Using cross platform metrics for determining user engagement

ABSTRACT

Systems, apparatuses, and methods are described for determining a consumer&#39;s engagement with a brand of the business by tracking the consumer&#39;s activities in multiple platforms, such as social media platforms, content platforms, gaming platforms, other retailers, streaming video providers, service providers, etc. Method are described for probabilistically granting users variations of items that are otherwise being acquired. The granting may be random, but probabilities may be boosted based on the consumer&#39;s activities in the platforms.

RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.16/580,641, filed Sep. 24, 2019, which claims priority to U.S.provisional application Ser. No. 62/861,691, filed Jun. 14, 2019, theentire contents of each are incorporated herein by reference.

FIELD OF THE TECHNOLOGY

The technology disclosed relates digital data processing and artificialintelligent systems and corresponding methods for reasoning withuncertainty (e.g., machine learning systems, and artificial neuralnetworks). In particular, the technology disclosed relates to digitaldata processing systems and methods for estimating and increasing userengagement in multiple platforms such as content platforms, gaming,retail, streaming video providers, social media, etc.

BACKGROUND

Increasing active engagement and brand loyalty in consumers is a commongoal for many businesses. A business may maintain a computing systemthat analyzes purchase histories of consumers at its online or physicalstores. The computing system may comprise various standards, triggers,conditions, and logical rules that are taken into consideration fordetermining points earned by the consumers based on their purchasehistories. The computing system may facilitate the process by which theconsumers can exchange the earned points for goods and services offeredby the business. Receiving free goods and services in exchange of earnedpoints may increase the consumer's engagement with the business.

Existing computing systems employed by businesses to increase consumerengagement may also take purchase histories of the consumers intoaccount. However, in order to do a more comprehensive study of theconsumer's engagement with the brand of the business, the consumersactivities in other platforms external to the business may need to betaken into account. Such platforms include social media, contentplatforms, gaming platforms, other retailers, streaming video providers,service providers, etc. Analyzing consumer behavior in other platformsmay require following use of different hardware devices, differentnetworks, different software applications, and services, etc. Featuresdescribed herein provide improved technology to increased user loyaltyand engagement with the brand.

SUMMARY

Systems, apparatuses, and methods are described for loyalty and rewardssystem that looks at a variety of factors. These factors may include,but are not limited to, how many times has this user purchased aparticular product, service, or used a particular supplier, how manyother services are used from one or more related suppliers, demographicsof user such as age, income, location, time of the day, environmentassociated with the interaction with the user, holidays, reoccurringsales, determinations of loyalty levels, social media interactions(e.g., Twitter, Instagram, Linkedin, Facebook), and other relevantfactors such as those associated with targeted advertising metrics, asdescribed in more detail below. A service provider can leveragecross-platform metrics to monitor, gauge, and encourage a user toimprove his or her loyalty score. A service provider may implement aprobabilistic rewards program in which a higher loyalty score increasesa user's probability of getting a better loyalty prize. The prizes canrange from modest items to extremely rare items that just can't bepurchased at all. For example, where a service provider owns and/orcontrols an extremely popular stadium, sports team, streaming game,content channel, etc., these assets may be used to generate highlysought after rewards and in some cases extremely rare and unique prizes.The extremely rare items can be leveraged to create a large “buzz” onsocial media and other outlets around the product or service and hencegarner large amounts of attention and free advertising for the productor service. The most loyal customers increase their odds of obtaining anextremely rare and valuable reward as well as more common less rarerewards. This helps build brand loyalty. Further, information obtainedfrom the loyalty and rewards program can then be provided to thecross-platform system confidentially in an anonymized manner to improvemetrics for such purposes as cross-platform targeted advertisements.

Creation of unique items made a special way, or a special experiencethat's not for sale, can generate a large amount of “buzz” (e.g., publicinterest). A user can increase his or her chances of obtaining one ofthese unique items (or a rarer item) through increasing his or herloyalty score. The items may be referred to as “loot.” Through this, itis possible to revolutionize the retail experience and associatedproducts and services in a way that glamorizes it, makes it fun, andgarners a large amount of free advertisement. Cross-platform technologycan automate many of these processes and find relevant metrics thatotherwise wouldn't be available. A loot server is proposed to track theloyalty of customers across multiple platforms such as contentplatforms, gaming, retail, sports teams (including e-sports teams),arenas, service providers, telecommunication providers, streaming videoproviders, social media, theme parks, etc. The loot server can thenpromote rewards via advertisements, joint promotional programs, and/ordirectly to the user across multiple platforms to build brand loyaltyand increase user engagement.

One way to make the “loot” even more valuable, is to eliminate theuncertainty associated with the loot in the secondary market. Forexample, if someone were to auction a “rare” baseball, there is a needto authenticate the signature or the ball—but there is no inexpensiveand reliable way to do this—particularly in the online market place.Today, the authentication process for extremely rare items is laborintensive and subject to fraud. The loot server described herein seeksto provide a simple and easy authenticity process for items that mayhave been procured through a loyalty mechanism, making sure they aren'tcounterfeit. This brings trust and increased value to the rare items. Italso promotes a secondary market place, making the rare and unique itemseven more valuable, which gives more incentive to participate in therewards program and builds brand loyalty.

A user who is purchasing an item, such as a sweatshirt, may have apercentage chance of being given an alternative, and rarer, version ofthat item, for example, a sweatshirt signed by a team member or evenrarer, every member of the team. The user's odds for being given therarer version may be based on a variety of factors, such as timing ofthe purchase, geography where the purchase is made, user behavior,purchase history, loyalty program/engagement factors, and/or otherfactors, that may encourage user engagement with the source of the item.In some instances, an extremely rare and unique experience such assitting with the team on the bench during a playoff game may be one ofthe top prizes. This may be awarded at the final game of the seasonbased on a drawing which has its probabilities modified by loyaltyfactors (e.g., season ticket holder status, promotions on social media,followers on social media, length of time being a fan, quality oftickets held such as box seats, amount of away games watched, retailpurchases of items from the team, and/or other loyalty factors).

Loyalty factors can range from metrics like have you shopped with usbefore, have you made purchases with us before, purchases within certaingeographic locations (purchases in a stadium in Philadelphia this weekand Universal Park the following week generates a probability bonus.Geolocation can be accessed from, for example, a mobile phone andpurchases may be tracked using a suitable mechanism such as APPLE PAY™or cooperative arrangements with retailers such as Amazon.com orNHL.com. Similarly, social components may provide a boost. For example,if you encourage your friends or followers to do or buy something(attend Universal Park or go to a Flyers game), there could be a boostgranted to you and your friends, but you all have to sign up and do itat the same time. Additionally, missions can be assigned to boostprobabilities such as going to a specified restaurant and take a photowith the restaurant owner, going to a soccer match and taking a photobehind the net, etc. These missions may be in either the real world orit could also be in the virtual world like once you get to a certainlevel of a game, you receive loyalty rewards or watched this X manyepisodes of a show. For example, if a team of Philadelphia Fusion fansachieve a difficult collective mission to achieve a virtual goal, theirodds of winning a rare item (e.g., box seats) at an associated Fusionevent may be increased. After the mission is completed andauthenticated, the users may receive a short term boost or a permanentboost depending on the complexity of the mission. Boosting factors(e.g., missions for restaurants) may be auctioned off to retailers usingcommon targeted software applications such as those offered by CanoeVentures and/or Google Ads/Google Display Network. For example, theowner of the advertised product or service (e.g., restaurant) maycontribute monetarily to the rare item in addition to paying for theopportunity to participate in the mission. An extremely rare item maygenerate a great deal of online “buzz” and hence a greater level ofexposure for the sponsor.

Each item may be offered in a variety of different versions, having avariety of different rarity levels. An item registry may track theownership of rare items, and allow users to verify ownership tofacilitate future transfers of the item. In one example, a loot servermaintains a title registry that allows user to record and tracktransfers of the rare item along with relevant authentication data suchas data associated with an embedded authentication tag in the item.

Systems and methods will be described in more detail herein that fosterloyalty and rewards systems and methods using cross-platform metrics(including sponsorship and rewards) to create a more robust echo systemto increase user engagement across a wide variety of products andservices and leverage online and social media “buzz” to maximize impactand minimize overall costs from a particular marketing campaign. Thesetechniques are particularly applicable to service providers whotypically offer a wide range of products and services.

This summary presents a simplified summary of certain features. It isnot an extensive overview and is not intended to identify key orcritical elements.

BRIEF DESCRIPTION OF THE DRAWINGS

Some features are shown by way of example, and not by limitation, in theaccompanying drawings. In the drawings, like numerals reference similarelements.

FIG. 1 shows an example communication network.

FIGS. 2A, 2B and 2C show an example sequence of screens for a purchasetransaction with probabilistic grant of item.

FIG. 3 shows an example screen of an item ownership registry.

FIG. 4 shows an example table of item variants and associated odds.

FIGS. 5A-B show an example user random value roll.

FIG. 6 shows an example listing of rules and/or conditions for randomvalue boosts.

FIGS. 7A, 7B, 7C, and 7D show an example algorithm for a probabilisticgrant of an item variant.

FIG. 8 shows example hardware elements of a computing device.

FIGS. 9A and 9B show architectural level schematics of environments thatinclude loot systems.

FIG. 10 illustrates an example loot system.

FIG. 11 illustrates an example boost monitor in the loot system.

FIGS. 12A, 12B, 12C, 12D, 12E and 12F are symbolic drawings indicatinghow the databases in the loot system in FIG. 10 are organized.

FIG. 13 is a sequence diagram illustrating a representative method ofprocessing a new user in the loot system.

FIGS. 14A and 14B illustrate a representative method of monitoring thelocation of a user by the boost monitor in the loot system.

FIG. 15 is a sequence diagram illustrating a representative method ofmonitoring a live sports event by the boost monitor in the loot system.

FIG. 16 is a sequence diagram illustrating a representative method ofmonitoring participants in a gaming platform by the boost monitor in theloot system.

FIG. 17 is a sequence diagram illustrating a representative method ofmonitoring purchase histories of users by the boost monitor in the lootsystem.

FIGS. 18A and 18B illustrate a representative method of monitoringsocial media accounts of users by the boost monitor in the loot system.

FIG. 19 is a sequence diagram illustrating a representative method ofmonitoring content viewing histories of users by the boost monitor inthe loot system.

FIG. 20 is a sequence diagram illustrating a representative method ofmonitoring photo uploaded by users by the boost monitor in the lootsystem.

FIG. 21 is a sequence diagram illustrating a representative method ofmonitoring health goals achieved by users by the boost monitor in theloot system.

FIG. 22 is a sequence diagram illustrating a representative method ofmonitoring calendar events by the boost monitor in the loot system.

FIGS. 23A and 23B illustrate a representative method of informing usersof available loot scores by the boost monitor in the loot system.

FIGS. 24A, 24B and 24C are sequence diagrams illustrating representativemethods of sending targeted advertisements for upcoming chances to winloot scores and loot items.

FIG. 25 is a sequence diagram illustrating a representative method ofreceiving a loot item during purchase of a common item from an internalretail store of the loot system.

FIG. 26 is a sequence diagram illustrating a representative method ofreceiving a loot item during purchase of a common item from an externalretail store.

FIG. 27 is a sequence diagram illustrating a representative method ofexchanging loot items in the internal retail store of the loot system.

FIG. 28 is a sequence diagram illustrating a representative method ofrequesting change in ownership of a loot item.

DETAILED DESCRIPTION

The accompanying drawings show examples of the disclosure. It is to beunderstood that the examples shown in the drawings and/or discussedherein are non-exclusive and that there are other examples of how thedisclosure may be practiced.

FIG. 1 shows an example communication network 100 in which a premises101 may be communicatively connected with a data center 102 to furthercommunicate with an external network 103. The communication network 100may comprise one or more information distribution networks of any type,such as, without limitation, a telephone network, a wireless network(e.g., an LTE network, a 5G network, a WiFi IEEE 802.11 network, a WiMAXnetwork, a satellite network, and/or any other network for wirelesscommunication), an optical fiber network, a coaxial cable network, theInternet, and/or a hybrid fiber/coax distribution network. The externalnetworks 103 may comprise networks of Internet devices, telephonenetworks, wired networks, wireless networks, fiber optic networks,and/or any other desired wired or wireless network including theInternet.

The communication network 100 may use a series of interconnectedcommunication links 104 (e.g., coaxial cables, optical fibers, wirelesslinks, etc.) to connect multiple premises 101 (e.g., businesses, homes,consumer dwellings, train stations, airports, etc.) to data center 102(e.g., a headend and/or AMAZON WEB SERVICES™ (AWS™)). The data center102 may send downstream information signals (towards premises 101) andreceive upstream information signals (from premises 101) via thecommunication links 104. Each of the premises 101 may comprise devices,described below, to receive, send, and/or otherwise process thosesignals and information contained therein.

An example premises 101 may comprise an interface 105. The interface 105may comprise circuitry used to communicate via the communication links104. The interface 105 may comprise a modem, which may comprisetransmitters and receivers used to communicate via the communicationlinks 104 with the data center 102. The modem may comprise, for example,a coaxial cable modem (for coaxial cable lines of the communicationlinks 104), a fiber interface node (for fiber optic lines of thecommunication links 104), twisted-pair telephone modem, a wirelesstransceiver, and/or any other desired modem device. A plurality ofmodems operating in parallel may be implemented within the interface105. The interface 105 may comprise a gateway 106. The modem may beconnected to, or be a part of, the gateway 106. The gateway 106 may be acomputing device that communicates with the modem(s) to allow one ormore other devices in the premises 101 to communicate with the datacenter 102 and/or with other devices beyond the data center 102 (e.g.,via the data center 102 and external network(s) 103). The gateway 106may comprise a set-top box (STB), digital video recorder (DVR), adigital transport adapter (DTA), a computer server, and/or any otherdesired computing device.

The gateway 106 may also comprise one or more local network interfacesto communicate, via one or more local networks, with devices in thepremises 101. Such devices may comprise, e.g., display devices 107(e.g., computer monitors, televisions, touch screens, etc.), phones 108(e.g., smartphones, cell phones, cordless phones (e.g., Digital EnhancedCordless Telephones—DECT), landline phones, Voice over InternetProtocol—VoIP—phones, etc.), computers 109 (e.g., desktop computers,laptop computers, tablet computers, notebooks, netbooks, etc.), gamingconsoles 110, STBs or DVRs 111, Internet-of-Things (IoT) 112 devices(e.g., smart watches, appliances, printers, home security devices, etc.)and/or any other desired communication device. The gateway 106 mayemploy any desired type of local network interface to communicate withthe devices at the premises 101. This may include wired interfaces(e.g., coaxial cable, Multimedia Over Coax Alliance (MoCA), Ethernetinterfaces, power line interfaces, Universal Serial Bus (USB) and/orwireless interfaces (e.g., Institute of Electrical and ElectronicsEngineers—IEEE—wireless protocols (IEEE 802.11, 802.15, etc.),Bluetooth, cellular phone, etc.). The various devices may be located atthe premises 101, or outside the premises but within range of a wirelessor wired connection.

The data center 102 may comprise an interface 113, such as a terminationsystem (TS). The interface 113 may comprise a cable modem terminationsystem (CMTS) and/or other computing device(s) configured to sendinformation downstream to, and to receive information upstream from, thepremises interface 105 (and devices 106-112). The interface 113 may beconfigured to manage communications among those devices, to managecommunications between those devices and backend devices such as servers114-116, and/or to manage communications between those devices and oneor more external network 103. The data center 102 may comprise one ormore network interfaces 117 that comprise circuitry needed tocommunicate via the external network 103. The external networks 103 maycomprise networks of Internet devices, telephone networks, wirednetworks, wireless networks, fiber optic networks, and/or any otherdesired network. The data center 103 may also or alternativelycommunicate with the premises devices via the interface 117 and one ormore of the external networks 103, e.g., via one or more wireless accesspoints 118 (e.g., cell phone towers, picocells, wide area wirelessnetworks, etc.).

The data center 102 may comprise various server computing devices tooffer various services to users. A content server 114 may be configuredto provide content to devices in the premises 101. This content maycomprise, for example, video, audio, text, web pages, images, files,etc. The content server 106 (or, alternatively, an authenticationserver) may comprise software to validate user identities andentitlements, to locate and retrieve requested content, and/or toinitiate delivery (e.g., streaming) of the content.

An advertisement server 115 may be configured to provide advertisementservices associated with the content provided by content server 114 (orany other content accessed by the devices 106-112). For example, theadvertisement server 115 may store and provide advertisement files to bepresented to users with audio and/or video (e.g., audiovisual) programs,Internet access, video games, etc. An advertisement server 115 may beresponsible for formatting and inserting advertisements in a videostream being transmitted to devices in the premises 101 and/or to thedevices 106-112. The advertisements may be targeted to users and/ortheir devices based on various demographic information, user contentconsumption history, device capabilities, and configurations, etc.Certain advertisements may only be available to users who have a certain“loot” score. For example, if the user has received enough award points,the user may be provided advertisements for certain unique or difficultto obtain items. The rewards points and associated loot score may bestored on a loot server 125. The potential for a reward increases theuser's desire to interact and/or engage with the ads because the usernever knows when a special offer will be forthcoming. It also encouragesthe user to share more information with the platform/service provider toincrease his/her odds of receiving an ad with a special promotion and/orother loot from the loot server 125.

An application server 116 may be configured to offer any other desiredservice. For example, an application server 116 may be responsible forcollecting, and generating a download of, information for electronicprogram guide listings which may list programs, video games, music,streaming services (games, video, audio, and various online services),and other services/applications. An application server may beresponsible for monitoring user viewing habits and collectinginformation from that monitoring for use in selecting advertisements.The services may include walled garden services. Walled garden servicesmay replicate services offered by external servers via the externalnetwork 103 but through a portal of the data center 102. So, forexample, an online retailer server 120 may offer a website for the saleof merchandise, and the data center 102 may replicate that functionalityusing one or more application servers 116. In providing local access tothe retailer 120, the data center 102 may tailor the experience to theuser based on the user's relationship with the data center 102 and/orthe user's reward points available from the loot server 125. The walledgarden services 119 may replicate services offered by various serversvia the external network 103, such as a retailer walled garden servercorresponding to retailer servers 120, a walled garden social mediaserver corresponding to social media servers 121, walled garden video ondemand server 119 c corresponding to video on demand servers 124, walledgarden video gaming servers 119 d corresponding to video gaming servers122 and/or electronic sports streaming 123, etc. In the walled garden,the user have its “loot” or rewards score from the loot server appliedto bolster his or her chances of obtaining more rare merchandise. Whilesharing of the “loot” or “rewards score” from the loot server 125 toplatforms outside of the walled garden (e.g., social media server(s)121, retailer server(s) 120, gaming servers(s) 122, eSports Streamingserver(s) 123, and/or video on demand server(s) 124 via externalnetwork(s) 103) may occur with proper authentication, the use of theloot or “rewards score” within the walled garden encourages users tostay on the desired platforms, which increases user loyalty. Wheresharing of the loot score occurs across external network 103, it may beshared with other service providers, retailers, gaming companies,eSports teams, Video service providers, etc. in a cooperative manner. Inthis way, certain rewards earned on partner networks may be creditedtoward the user's loot score. The partner networks may have acooperative arrangement with the service provider and/or may sharerevenue and/or platform support such as through an entity such as CanoeVentures.

The servers 114-116, 119 a-d, 125, 120-124, and/or other servers, may becomputing devices and may comprise memory storing data and also storingcomputer executable instructions that, when executed by one or moreprocesses, cause the server(s) to perform the various steps describedherein.

FIGS. 2A-C show example display screens that may be presented to a useras part of a purchase from an online retailer 120. The user may use adevice, such as computer 109, and navigate to the retailer 120 website(e.g., through the external network 103, or via the content providerwalled garden 119), and select an item to purchase. FIG. 2A shows anexample item detail screen 200. The item detail screen 200 may showvarious details of the item (e.g., a sweatshirt) that the user haschosen to view, and a button 201 to add the item to the user's shoppingcart for purchase. FIG. 2B shows an example checkout screen 202,indicating that the user has added the item to their shopping cart forcheckout. If the user may select the checkout button 203, the system maythen perform a probabilistic determination of whether the user will begranted a rare variant version of the chosen item. The probabilisticdetermination may entail generating a probability value for the user(e.g., a random number roll, similar to a roll of dice), and determineif the probability value falls within a predetermined value for receiptof the rare variant version. Details of this process are describedfurther below.

If the user is lucky, and the system may determine to grant the user therare variant version of the selected item, then the user may bepresented with the variant grant screen 204 shown in FIG. 2C. Variantgrant screen 204 may inform the user that they have been selected toreceive a rare variant version of the item they had selected forpurchase. This grant of a rare variant may be referred to as a ‘loot boxaward,’ and the variant grant screen 204 may comprise additionaldescriptive information explaining the variant that the user has beenselected to receive. For example, the variant grant screen 204 indicatesthat the user has been selected to receive the “Captain Star VariantHoodie,” which includes an additional “Captain's Star” breast patch, asillustrated in the image of the item in FIG. 2C (as compared to thenormal version shown in FIGS. 2A and 2B). There may be multipledifferent variations that are available, having different degrees ofrarity, and that degree of rarity may be indicated in the variant grantscreen 204. The variant item may also be of limited production (e.g.,only 10,000 copies produced), and the production may be indicated aswell. Additional details of the rarity will be discussed further below.

If the user would prefer to have the original version of the iteminstead, the user may decline the offer of the variant. For example, theuser may simply select the “No Thanks” button 205 to decline, or the“Great!” button 206 to accept and purchase the variant item. Accepting arare item may alter the probability value for the rewards score in thecase where it is desired to spread the loot to multiple participants(e.g., making the rare item easier to obtain by other users). After theuser has won a rare item, it may be desirable to have the user buildadditional loyalty points to again reach the same level. The loot servermay also be configured to simply allow the probability mechanism tocontrol the awards without adjusting the user's loyalty points after theaward of a rare or unique item.

The loot offered to the user may also vary depending on the user'sdemographics. For example, if the user has demographics indicating he orshe may be more interested in an alternative loot, the loot may becustomized to be more appealing to the user's preferences. For example,this may be a favorite player or a cross-platform interest such assomething related to other content such as something related to aUniversal studios product or a favorite show.

Ownership of the variant item may be tracked, and this may facilitatesubsequent transfers of the item, as users may choose to sell theirvariants as collectible items on a marketplace (e.g., retailer server120, loot server 125, and/or another online marketplace). For example,the user may be given the option of auctioning off the rare variant on amarketplace (e.g., the loot server 125) or posting the receipt of therare variant on social media—thus creating increased buzz concerning theloot program and the rare variant. FIG. 3 shows an example ownershipscreen 300, or loot registry, for the variant item. The ownership screen300 may be accessed, for example, via a web page offered by the lootserver 125 and/or retailer server 120, and users may enter an itemserial number to see an ownership history 301 listing the various ownersof the item and their dates of ownership. The ownership screen 300 mayprovide an option 302 to record a new transfer, and a user may choosethis option to log in (e.g., with a username and password) and enterinformation to update the history to indicate a new transfer ofownership. The ownership screen 300 may provide users with confidence ifthey are choosing to acquire a rare item.

FIG. 4 shows an example table 400 indicating various item variants andtheir corresponding details and odds for acquisition. The table listsseveral items (Hoodie, Jersey, T-Shirt, and Hat), and indicates theirrarity. The rarity may be indicated using a simple name for ease ofreference (e.g., Common, Good, Rare, Superior, Epic, Legendary), andeach rarity may include a probability roll value. In the FIG. 4 example,the probabilities are shown as percentages, reflecting a random numberbetween 0 and 100.0. A random number roll may be performed for a userwho is purchasing an item, and the resulting random number (e.g.,between 00.0 and 100.0) may be compared against the table 400 todetermine which version of an item the user may receive. Using theHoodie sweatshirt example, a random value between 00.0 and 91.9 mayresult in the user being granted the Common (e.g., an ordinary,unchanged) version of the item. A random value between 92.0 and 97.9 mayresult in the user being granted the Good version of the item. In theFIG. 4 example, the Good version of the Hoodie sweatshirt may includethe Captain Star shown in FIG. 2C.

A random value between 98.0 and 99.0 may result in the user beinggranted the Rare version of the sweatshirt, which may include a coloroutline of a player number on the sweatshirt. A random value between99.1 and 99.5 may result in the user being granted the Superior versionof the sweatshirt, which may include an alternate color on the interiorof the sweatshirt's hood. A random value between 99.6 and 99.8 mayresult in the user being granted the Epic version of the sweatshirt,which may include an additional team logo, and a random value between99.9 and 100.0 may result in the user being granted the Legendaryversion of the sweatshirt, which may include a player autograph. Ofcourse, the values and details in FIG. 4 are merely examples, and otherprobabilities, variations, and items may be used. Different items mayhave different probabilities, items may have greater or fewer numbers ofvariants than other items, and other modifications may be made asdesired.

FIGS. 5A & 5B show an example random value roll for a user, and theeffect of a boost that may be applied to the roll. FIG. 5A shows thetable 400 and a sample random value roll of 91.3 for a user. Asindicated in the example table 400, a random value of 91.3 would merit aCommon version of an item. However, certain factors may give the user aboost to their random value. FIG. 5B shows the user receiving a +2.0%boost to their random value roll, which has increased their random valueby 2.0% of its original value, resulting in a boosted value of 93.13. Inthe illustrated example of FIG. 5B, the boosted random value of 93.13 issufficient to qualify the user for receipt of a Good variant of theitem, instead of the Common item that was originally selected. Theenticement of receiving a rare version of an item, and the ability toreceive random value boosts, may serve to increase a user's engagementwith a source of the item (e.g., a professional esports team). Further,where appropriate, the rewards and loot items may be available withcross-platform support such that loot factors and associated loot may beearned and redeemed across different platforms owned, licensed, and/orcontrolled by a service provider. In this way, the loot and loyaltyrewards may be customized to be more appealing to a particular userdemographic and may be tied in with various advertising and promotionssuch as through the Canoe Ventures system.

FIG. 6 shows an example boost table 600, listing various boosts that maybe applied to a user's random value roll. For example, a 2% boost may beawarded if the user completes their purchase (e.g., proceeds through thecheckout process, completes an ordering process to acquire the item evenwithout purchase) within 10 minutes of when a player on an esports teamrecords a predetermined achievement (e.g., recording a 15+ kill streak)in a competition match. Another 3% boost may be awarded if the usercompletes their purchase while the user is located in a city that ishosting a professional esports match, and if the purchase is completedwhile the match is ongoing (or within a predetermined period afterward).Some boosts may comprise multiple conditions in the form of missions, inwhich a user must complete a sequence of events (e.g., run a mile withyour health tracker, and complete level 10 of an identified video game).The determination and application of these boosts may rely oncommunications with other services, such as an esports streaming server123, gaming server 122, or other devices, and additional details will bediscussed with FIGS. 7A and 7B below.

FIGS. 7A and 7B show an example algorithm for a probabilistic grant ofan item variant. The various steps may be performed by the retailerserver 120, application server 116, or any other desired computingdevice. In step 701, the process may begin with storing loot information(e.g., in loot server 125) indicating the various items, their variants,descriptions of the variants, their associated odds of acquisition, andrarity. The table 400 may be an example of this loot information. Thecreation and storage of the loot information may be performed by a useradministrator, although some or all may be created automatically aswell.

In step 702, boost information indicating various random value boostsmay be stored. The FIG. 6 boost table may be an example of the boostsindicated by this boost information. The boost information may indicatea boost by name, its amount of boost, and the various rules and/orconditions that may be used to determine if a user is to be awarded aparticular boost. The FIG. 6 boost table shows a textual description ofthe rules and/or conditions, and the boost information may also comprise(or indicate) computer-executable instructions for applying the rulesand/or conditions. For example, computer-executable instructions mayindicate an address of a process or server that maintains stateinformation for a particular match (e.g., player performanceinformation, game status, game location, etc.), a user's purchasehistory (e.g., times, places, items, prices, etc. associated with pastpurchases), a user's demographic information, a user's exercise history,a user's social network (e.g., number of followers, identification offriends, etc.), and/or any other information source for applying adesired rule and/or condition, and may comprise instructions forretrieving the necessary information and applying the rule or condition.

In step 703, a determination may be made as to whether a new user hasrequested to register to participate in the probabilistic grant ofitems. A new user request may be made in a variety of ways. A new usermay use a web browser to access a retailer server 120 web site, and theweb site may comprise an option for new users to register, e.g., on lootserver 125, which the user may use to create a new account and registerto participate. A user may be added at a retail establishment, such aswhen making a purchase at a sporting goods store. The user may beassigned an electronic rewards “card” such as a cookie, profile, orother tag in a mobile phone and/or tagged to a user's account/profile ata service provider.

If a new user request has been received, then in step 704, a new accountmay be created for the user. This may comprise requesting and storinguser information identifying the user and information that may be usedto determine if any rules or conditions are satisfied. For example, theuser information may identify an address (e.g., email address, deviceaddress, phone number, etc.) that can be used to obtain informationindicating the user's current geographical location (e.g., by requestingGPS information from a user's smartphone), the user's purchase history,the user's social network, and various information discussed above. Theuser information may indicate the user's preferences, such as a favoritesports team, favorite team member, etc., which can be used to determinethe user's eligibility for satisfying certain boost rules or conditions.The creation of the account may also comprise granting the loot serverand/or retailer server 120 access to various sources of informationneeded for the random value boosts shown in the boost table 600. Forexample, the user may provide access credentials (e.g., username,password, etc.) for obtaining information from a fitness trackingapplication, social media account, purchase history, GPS information,etc.

In step 705, a determination may be made as to whether a registered userhas requested to purchase an item that is subject to the probabilisticvariant grant described herein (e.g., an item for which there arevariants and probabilistic rules in table 400. This may occur, forexample, if the user selects the checkout button 203 in an onlinepurchase, or if the user otherwise acquires a new item from the retaileror its server 120. The acquisition is described above as a purchase, butit need not be a purchase. Any type of acquisition, such as a free giftor other reward, may qualify for a chance at an item variant.

In step 706, available variants of the item may be determined, and theassociated rules from table 400 may be retrieved for use in determiningwhether the user will be eligible to receive a variant.

In step 707, an initial loot roll value (e.g., an initial probabilityvalue) may be determined for the user's purchase transaction. As notedabove, the initial probability value may be a random value between 00.0and 100.0. These values are merely examples, though, and any desiredrandom value generation may be used. From the example shown in FIG. 5A,the user may have received an initial random value of 91.3. If the userhas selected multiple items for purchase, a separate initial probabilityvalue may be determined for each item, or a single initial probabilityvalue may be determined for the entire purchase (e.g., one probabilityvalue for all items in the user's checkout cart).

In step 708, one or more boost factors may be applied to the initialprobability value(s) from step 707. FIG. 7B illustrates a detailed viewof an example algorithm for applying these boost factors. In step 709, adetermination may be made as to whether a geographic boost is availablefor the item being purchased. The boost table 600 may indicate that oneor more boosts are based on geographic information. For example, a boostmay grant a 3% increase to the probability value if the purchase iscompleted from a location that is in a city that is hosting a sportingmatch or tournament. If such a geographic boost is available, the boosttable 600 may indicate the geographic condition (e.g., identifying a ZIPcode, GPS coordinate range, town, etc.), and in step 710, the purchasinguser's geographic location may be determined. This may be performed, forexample, by sending a request to a user's GPS-equipped smartphone,asking for the smartphone's current location. The location may bedetermined by performing a lookup based on the Internet Protocol (IP)address of a computing device that the user is using to complete thepurchase transaction.

In step 711, a determination may be made as to whether the geographiccondition (or conditions, if multiple geographic conditions areavailable) is satisfied. This may comprise, for example, determiningwhether the user's GPS coordinates are within an identified range of GPScoordinates from the boost table 600, or if the user's ZIP code (whichmay be entered by the user as part of the checkout process) matches aZIP code identified in the boost table 600. If the geographic conditionis not satisfied, then the process may proceed to considering the nextboost condition in step 713. However, if the geographic condition issatisfied, then in step 712, the corresponding boost may be applied tothe user's probability value. For example, a user's initial probabilityvalue of 91.3 may be increased by 3% to reflect the application of theboost. Other boosts described below may be applied in the same way, andin an accumulating fashion for all applicable boosts whose conditionsare satisfied.

In step 713, a determination may be made as to whether a live matchboost is available in the boost table 600. A live match boost mayindicate a condition that is based on one or more events occurring in,or status of, a particular event such as an esports match. For example,a live match boost may require that a purchase is completed while anesports match is ongoing, or during halftime of the match (a particulartime point in the match), or within a predetermined time range of anevent occurring in the match (e.g., within 10 minutes of a particularteam's player recording a 15+ kill streak in a match, or within 15minutes of a conclusion of a championship win, etc.). If no live matchboost is available, then the process may proceed to step 717 and processthe next boost type. If a live match boost is available, then in step714, a request may be sent to a computing device that tracks the currentprogress of games. For example, retailer server 120 may send a messageto eSports streaming server 123, requesting information indicating thecurrent state of a particular esports match that is relevant to theavailable game state boost (e.g., the killstreaks attained, the players'statistics, the game's score or time remaining, etc.). The game stateinformation may be obtained in a variety of other ways. For example, theretailer server 120 may subscribe to a real-time data feed that providesup-to-date information regarding events, such as services that provideplayer statistics for fantasy football during live football games.

In step 715, a determination may be made as to whether the game stateinformation satisfies the condition(s) associated with a live matchboost. If a condition is satisfied (e.g., a time associated with acurrent purchase falls within a 15-minute window following theconclusion of a championship match), then in step 716 the correspondingvalue boost may be applied to the user's probability value.

In step 717, a determination may be made as to whether a purchasehistory boost is available in boost table 600. For example, a purchasehistory boost may grant a boost based on a quantity of purchases made bythe user within a time period, such as the previous 90 days. Thepurchases may be made via retailer server 120, or via any otherassociated service in communication with the retailer server 120. If nosuch boost is available, then the process may proceed to step 721 toprocess the next boost type. If a purchase history boost is available,then in step 718, the user's purchase history may be determined. Thismay be accomplished, for example, by examining a profile or user record,for the user, maintained by the retailer server 120.

In step 719, a determination may be made as to whether the purchasehistory boost condition is satisfied (e.g., if the user has made one ormore purchases in the last 90 days). If such a condition is satisfied,then in step 720 a corresponding boost may be applied to the user'sprobability value.

In step 721, a determination may be made as to whether a social networkboost is available in boost table 600. A social network boost may granta boost if one or more social network conditions are satisfied. Forexample, one social network boost may be granted if the user has aminimum number of followers or friends on a social network platform.Another social network boost may be granted if one or more of the user'sfriends have also made a purchase. If a social network boost isavailable, then in step 722, the relevant social network data may beretrieved. This retrieval may comprise sending a request to a socialmedia server 121, requesting information regarding the user's socialmedia account (e.g., number of followers or identity of friends).

In step 723, a determination may be made as to whether the user's socialmedia data satisfies the relevant social media boost condition(s). Forexample, it may be determined that the user has a quantity of friends orfollowers that exceeds a minimum number indicated in the social networkboost condition. If the social network boost condition is satisfied,then in step 724, the corresponding boost may be applied to the user'sprobability value.

In step 725, a determination may be made as to whether a calendar boostis available in boost table 600. A calendar boost may grant a boost ifthe purchase is made during certain predetermined time periods. Forexample, a boost may be granted if the purchase is made after 6 pm onThanksgiving, on the user's birthday, or after the user's 1-yearanniversary since registering for the probabilistic grant service. If acalendar boost is available, then in step 726, the relevant calendardata may be retrieved. This may comprise retrieving the current date, alist of holidays, the user's birthday or date of registration, etc.

In step 727, a determination may be made as to whether any calendarboost conditions are satisfied, and if so, then in step 728 thecorresponding boost(s) may be applied to the user's probability value.

In step 729, a determination may be made as to whether a health boost isavailable in the boost table 600. A health boost may require certainhealth monitoring characteristics of the user. For example, if a userperforms a physical feat, such as running a mile in under 8 minutes, orexercising for 7 consecutive days, then the user may be granted a healthboost to their probability value. If a health boost is available, thenin step 730, the user's health monitoring data may be retrieved. Thismay be accomplished, for example, by sending a request to a healthmonitoring app or a fitness tracker used by the user.

In step 731, a determination may be made as to whether any health boostconditions are satisfied. If any such conditions are satisfied, then instep 732, the corresponding boost(s) may be applied to the user'sprobability value.

In step 733, a determination may be made as to whether any photographicboosts are available in the boost table 600. A photographic boost mayrequire that a user provide a certain image (e.g., photograph) as partof the purchase transaction. For example, users may be encouraged totake a picture of themselves, a “selfie,” at the site of a game, or withmerchandise supporting their favorite esports team. To help withidentification, a quick reference (QR) code may be provided at the siteof a game, or on certain merchandise, and the user may take a photographof themselves with the QR code in the photograph. The user may thenupload the photograph as part of the purchase transaction, such as byusing an “Upload Photo for Loot Boost” option 207 in the checkout screenof FIG. 2B.

If a photographic boost is available, then in step 734, the relevantphotographic data may be retrieved. This may comprise, for example,retrieving a selfie photograph that the user uploaded, and accessing adatabase of approved QR codes. Object recognition may also be used(e.g., encouraging users to take photographs of certain kinds ofobjects, such as an animal based on a sports team mascot), and adatabase of recognized objects may also be retrieved in order to performobject recognition on a photograph that the user uploaded.

In step 735, a determination may be made as to whether the user'suploaded photograph satisfies the photo condition(s) (e.g., if arequired QR code or object is recognized in the photograph). If a photocondition is satisfied, then in step 736, a corresponding boost may beapplied to the user's probability value.

In step 737, a determination may be made as to whether a network boostis available in the boost table 600. A network boost may be grantedbased on network conditions. For example, the network boost may begranted if the user making the purchase is accessing the retailer server120 via a certain network provider, or if the user is making thepurchase via a walled garden service 119 that corresponds to theretailer server 120. A network boost may reward users who subscribe toparticular wireless carrier services.

If a network boost is available, then in step 738 relevant network datamay be determined. This may comprise, for example, determining a user'swireless carrier, Internet Service Provider (ISP), content/servicesubscriptions, network speed or bandwidth, etc. In step 739, adetermination may be made as to whether the determined network datasatisfies any network boost conditions indicated in the boost table 600.In the FIG. 6 example, a user may receive a +0.75% boost if the purchaseis completed via a particular ISP (ACME). If a network boost conditionis satisfied, then in step 740, a corresponding boost may be applied tothe user's probability value.

In step 741, a determination may be made as to whether a content historyboost is available in the boost table 600. A content history boost maybe granted based on the purchasing user's prior usage of content. Forexample, a content history boost may be granted if the user watches apredetermined minimum number of episodes in a video program, or if theuser has achieved a certain progress level in playing a video game(e.g., reaching a point in the game, completing the game, playing a gamefor at least 40 hours, receiving an achievement or trophy, etc.).

In step 742, a user's relevant content history may be retrieved. Thismay comprise, for example, sending a request to a gaming server 122 (ora gaming server in walled garden 119) along with (if desired) accesscredentials. The gaming server 122 may verify the credentials andrespond to the request by providing information indicating the user'sviewing history, video game history, etc. as needed to determine whetherthe content history boost conditions are satisfied.

In step 743, the content history information may be compared with thecontent history boost conditions, and if a condition is satisfied, thenin step 744 a corresponding boost may be applied to the user'sprobability value.

The above discussion addresses several example types of boosts andconditions that may be applied, but those are merely examples, and othertypes may be applied as well. Also, the various boosts and conditionsabove may be applied in combination as well. For example, a single boostmay comprise geographic and match state conditions. A single boost maycomprise geographic, match state, and social media conditions. Any ofthe examples above may be used in combination.

In step 745, the user's probability value, to which the variousapplicable boosts have been applied, may then be compared against a loottable 400 to determine whether the user is to be granted a variant ofthe item(s) selected for purchase. In the FIG. 4 example loot table 400,a boosted probability value between 00.0 and 91.9 would result in novariant being granted. If no variant is to be granted, then in step 746the user's purchase (or other item acquisition transaction) may beprocessed as normal. For example, the user may proceed to providepayment information and confirm the purchase, and the item would beprocessed for delivery pursuant to the purchase terms (e.g., arranged tobe delivered via a selected shipping procedure, shipped, etc.).

In the FIG. 4 example table 400, a boosted probability value between92.0 and 100.0 would result in the user being granted a variant of theitem that was selected for purchase. If the user is lucky enough to begranted a variant, then in step 747 the user may be alerted to the luckyevent. The user may be presented, for example, with the screen 204,which may inform the user the details of the variant item. In the FIG. 4example, the screen 204 indicates the original product details, and addsdetails regarding the rarity, production run, and product differences ofthe variant item that the user has been granted.

The user may be presented with an option to accept 206 or decline 205the variant item, and in step 748 a determination may be made as towhich option the user has chosen. If the user prefers to receive theoriginal item instead of the variant, then the user may choose todecline the variant, and in step 746 the purchase of the common itemwould be processed. If the user prefers to accept the variant item, thenin step 749 the user's profile data may be updated to indicate that theuser has acquired the variant item. In step 750, the item registry mayalso be updated to indicate that the user has acquired the variant item.The registry may be updated to indicate the user identification (e.g.,username), the date and/or time of the acquisition, and descriptivedetails of the item variant that the user has acquired. The registry maycomprise the information shown in the ownership history screen 300 foreach variant item.

In step 751, the purchase of the variant item may be completed. This maycomprise the same steps as in the normal purchase 746, althoughadditional treatment of the variant item may be provided. For example,the shipping may be performed using a different method (e.g.,prioritized delivery as opposed to standard delivery), the packaging ofthe variant item may be different (e.g., different labeling, colors toindicate variant), etc.

A user may wish to transfer ownership of the variant item. For example,rare variant items may be collectible and desirable, and demand may behigh on a secondary or resale market. In step 752, a determination maybe made as to whether a title transfer request has been received. A usermay have decided to offer their rare variant item for sale, for exampleon a secondary reseller site or auction site, and the user may log intothe retailer server 120 to request an update in the ownership status.The user may view the item registry screen 300, and may select a RecordNew Transfer option to enter details (e.g., date, time, new owner, etc.)for a transfer of ownership of the variant item. The reseller site(which may be retailer server 120 or another similar server) may beprovided with the selling user's authentication information as part ofthe sale listing for the variant item, and the reseller site mayautomatically log into the retailer server 120 and update the ownershipinformation as part of processing a resale transaction of the variantitem. A new user purchasing the item from the reseller site may providethe reseller site with their own identification information (e.g.,username), and may also provide authentication credentials for retailerserver 120 if the new user also has an account.

If a title transfer request has been received in step 752, then in step753 a validation determination may be made to verify that the request islegitimate. The validation may comprise requesting and receiving ausername and password from the user, as well as information identifyingthe variant item (e.g., a serial number, item number, name, etc.). Theitem registry may be checked to determine if the identified user isindeed the current registered owner of the identified item, and thepassword may be checked to verify that it is the correct password forthe user. Other forms of validation and/or authentication, such assecurity certificates, biometric (e.g., fingerprint, optical, facialrecognition, etc.), and others may be used as well for validating theuser identity.

If the validation fails, then in step 754 the title transfer request maysimply be denied. If the validation is successful, then in step 755 theitem registry may be updated to indicate the new owner and the date/timeof the transfer. Other details, such as the sale price, may also bestored in the item registry.

In step 756, a user's general loyalty level may be updated using anyand/or all of the various boosts discussed above (e.g., purchase historyboost 717, social network boost 721, etc.). The user may be providedwith an option to view their own loyalty status, and see the currentboost(s) that would be applied if they were to make a purchase. Thisvisibility may further encourage participation in the various boostingevents, as the user may be encouraged to increase their boost level forfuture purchases, and may be informed as to new missions, quests, boostconditions, etc. to pursue.

As may occur with item acquisition transactions, users may sometimeschange their mind about an item. A user who has received a rare variantitem may request to return the item for a refund. In such a situation,the user may be given the option to apply their boosted probabilityvalue towards obtaining a different item. For example, a user whoreceived a rare variant of a sweatshirt, may later (either afterreceiving the item, or even earlier such as in step 748 when acceptingthe item) decide to obtain a different item instead. To help avoidabuse, the application of a user's boosted probability value may belimited to items having an equal or lesser cost of the original itemthat was purchased. For example, if a user purchases a low-cost itemsuch as socks, and gets a lucky probability value, the user may beentitled to receive a Legendary rarity version of the socks. But if theuser wishes to exchange the socks for a more expensive item, such as asweatshirt, the user may be limited to receive only a common version ofthe sweatshirt because the sweatshirt is more expensive than the socks.The probability value, which may be stored as part of the retailer'srecord of the transaction, may be adjusted based on a difference in costor value between the exchanged item and its replacement, to determinewhether the user will receive a variant version of the replacement item.

To further facilitate user engagement, some users may be given theoption of giving advance approval to automatically purchase a particularvariant item if the user satisfies certain conditions associated withthe variant. For example, a user may request to automatically purchase aparticular player's variant sweatshirt if a boost condition involvingthat player (e.g., scoring a minimum number of points in a match) issatisfied.

FIG. 8 shows hardware elements of a computing device 800 that may beused to implement any of the computing devices shown in FIG. 1 and anyother computing devices discussed herein. The computing device 800 maycomprise one or more processors 801, which may execute instructions of acomputer program to perform any of the functions described herein. Theinstructions may be stored in a read-only memory (ROM) 802, randomaccess memory (RAM) 803, other memory media 804 (e.g., a USB drive, acompact disk (CD), a digital versatile disk (DVD)), and/or in any othertype of computer-readable medium or memory. Instructions may also bestored in an attached (or internal) storage (e.g., a solid-state harddrive, disc hard drive, etc.) or other types of storage media.

The computing device 800 may comprise one or more video output options.For example, a two-dimensional video output circuit 805 may providevideo output signals to a two-dimensional display device 806 (e.g.,television, display monitor, integrated display, etc.), which maycomprise a touch sensitive screen 807. A three-dimensional video outputcircuit 808 may provide stereoscopic video output signals to astereoscopic three-dimensional display 809 having left- and right-eyedisplay capabilities, such as a head-worn display, goggles, or otherstereoscopic display. Audio outputs may also be provided by audio outputcircuitry 810 to various speakers 811.

The computing device 800 may comprise various input devices, such as awired or wireless remote control 812, keyboard and mouse 813, video gamecontroller 814, etc. A microphone 815 may capture audio sounds, and acamera 816 may capture video images. Anaccelerometer/gyroscope/altimeter 817 may provide acceleration,orientation, and altitude information for interaction involving tiltingor moving the computing device 800. A global positioning system (GPS)818 may determine a geographic location of the computing device 800.

The computing device 800 may also comprise one or more networkinterfaces to communicate with local and/or remote external devices. Awired interface 819 may comprise Ethernet, Universal Serial Bus (USB),coaxial, optical fiber, radio frequency (RF), power line network, etc.wired connections to various devices and networks, and a wirelessinterface 820 may comprise cellular (e.g., 2G, 3G, 4G, LTE, 5G, etc.),wi-fi, IEEE 802.11, WiMax, Bluetooth, satellite, etc. wirelessconnections to various devices and networks. The network interfaces819/820 may comprise a modem to modulate and demodulate data fortransmission and receipt.

The computing device 800 may also comprise other sensors, such as amagnetometer, a digital compass, a proximity sensor, an ambient lightsensor, a pedometer, a barcode/QR code sensor, a barometer, athermometer, an air humidity sensor, a heart rate sensor, a biometricsensor (e.g., a fingerprint sensor, an eye scanner), a Near-FieldCommunication (NFC) receiver, etc. The computing device 800 may alsocomprise a radio signal receiver, such as an FM tuner.

Although FIG. 8 shows an example hardware configuration, it is only anonlimiting example. The illustrated elements may be combined,duplicated, separated, and otherwise altered as desired. One or more ofthe elements of the computing device 800 may be implemented as softwareor a combination of hardware and software. Modifications may be made toadd, remove, combine, divide, etc. components of the computing device800. Additionally, the elements shown in FIG. 8 may be implemented usingbasic computing devices and components that have been configured toperform operations such as are described herein. For example, a memoryof the computing device 800 may store computer-executable instructionsthat, when executed by the processor 801 and/or one or more otherprocessors of the computing device 800, cause the computing device 800to perform one, some, or all of the operations described herein. Suchmemory and processor(s) may also or alternatively be implemented throughone or more Integrated Circuits (ICs). An IC may be, for example, amicroprocessor that accesses programming instructions or other datastored in a ROM and/or hardwired into the IC. For example, an IC maycomprise an Application Specific Integrated Circuit (ASIC) having gatesand/or other logic dedicated to the calculations and other operationsdescribed herein. An IC may perform some operations based on executionof programming instructions read from ROM or RAM, with other operationshardwired into gates or other logic. Further, an IC may be configured tooutput image data to a display buffer.

While FIGS. 7B-7D illustrate various boosts that a user may receive,additional examples include, but are not limited to, the following: 1)how many times has this user purchased a particular product (e.g.,higher boost if the user purchases a particular product more than a 10quantity of times), 2) the cost of the purchased product or service(e.g., different boosts for basic vs. higher tiers of cost), 3) theparticular supplier (e.g., different boosts for different suppliers of aparticular product or service), 4) how many other services are used fromone or more related suppliers (e.g., higher boost if the user subscribesto services from a predetermined set of service providers), 5)demographics of user such as age, income, location, time of the day, 6)environment associated with the interaction with the user such asin-stadium purchases or in-theme park purchases, 7) holidays (e.g.,Christmas bonus), 6) reoccurring sales (e.g., high VOD purchases), 8)determinations of loyalty levels (e.g., strong positive feelings towardthe service provider), 9) social media interactions (e.g., higher boostfor positive feedback via Twitter, Instagram, Linkedin, Facebook, etc.),and 10) other relevant factors such as those associated with targetedadvertising metrics. A service provider can leverage cross-platformmetrics such as use of wireless, home security, solar, universal parks,and other products and services offered by the service provider. Aservice provider can monitor using an anonymized server to gauge, andencourage a user to improve his or her loyalty score. A service provideroffering Internet service may use deep packet inspection techniques tomonitor a user's data traffic, and may use this traffic to adjust theuser's boost values as described above.

A user who creates a large “buzz” on social media and other outletsaround the product or service can obtain a positive feedback effect andincrease his or her odds of winning another rare item. The “buzz” factorcan be feedback into the loyalty probability algorithm as a boostfactor, such as in evaluating the social network boost 721, and henceincrease the user's probability of receiving another rare item. This, inturn, increases the chances of generating more attention and freeadvertising for the product or service.

Information obtained from the loyalty and rewards program can then befeedback into the cross-platform system confidentially in an anonymizedmanner to improve metrics for such purposes as cross-platform targetedadvertisements. For example, where the user chooses a rarity itemassociated with a particular character or particular sports team, theymay be used to provide more relevant advertisements to the user such asads associated with the sports team or new shows featuring thecharacter.

Cross-platform technology can automate the loot processes and findrelevant metrics that otherwise wouldn't be available. For example, theloot server 125 may be configured and enable by the user to track brandloyalty of customers across multiple platforms including such items ascontent, gaming, retail, sports teams (including e-sports teams),arenas, service providers, telecommunication providers, streaming videoproviders, social media, theme parks, etc. The loot server 125 can thentransmit rewards via advertisements, retail purchase pages, jointpromotional programs, and/or directly to the user across multipleplatforms including streaming games and video programs to build brandloyalty and increase user engagement.

The loot server 125 may track loyalty factors inside and outside thewalled garden 119 using metrics like have you shopped with us before,have you made purchases with us before, purchases within certaingeographic locations (purchases in a stadium in Philadelphia this weekand Universal Park the following week generates a probability bonus).The loot server 125 can also (with user permission) use geolocationinformation in, for example, a mobile phone or smartwatch and variouspurchases such as using APPLE PAY™ or cooperative arrangements withretailers such as Amazon.com or sports teams like NHL.com. Similarly,social components may provide a boost to the user within loot server125. For example, if you encourage your friends or followers to do orbuy something (attend Universal Park or go to Flyers game), there couldbe a boost towards granted to you and your friends, but you all have tosign up and do it at the same time—which allows the loot server toincrease your boost score. Additionally, the loot server 125 may workcooperatively with other servers (e.g., each of the servers within thewalled garden 119) and/or content server 114, advertisement server 115,application server 116, social media server 121, retail server 120,gaming server 122, eSports streaming server 123 and/or video on demandserver 124 to create missions that can be assigned to a user or groupsof users (e.g., e-sports teams) to boost probabilities such as going toa specified restaurant and take a photo with the restaurant owner, goingto a soccer match and taking a photo behind the net, etc. The lootserver 125 and/or advertisement server 115 may structure these missionsin either the real world or in the virtual world like once you get to acertain level of a game, you receive loyalty rewards or watched this Xmany episodes of a show. For example, if a team of Philadelphia Fusionfans achieve a difficult collective mission to achieve a virtual goal,the loot server 125 may increase their odds of winning a rare item(e.g., box seats) at an associated Fusion event. Once the mission iscompleted and authenticated, the loot server 125 may provide a boostwhether it's a short term boost or a permanent boost depending on thecomplexity of the mission. The loot server 125 may be configured toallow boosting factors (e.g., missions for restaurants) to be auctionedoff to retailers using common targeted software applications such asthose offered by Canoe Ventures and/or Google Ads/Google Display Networkvia the advertisement server 115. For example, the owner of theadvertised product or service (e.g., restaurant) may contributemonetarily to the rare item in addition to paying for the opportunity toparticipate in the mission. The advertisement server 115 may communicatethese opportunities to various cross-platform entities and then feedbackthe opportunities to the loot server along with a shared revenue stream.For example, the loot server 125 may offer an extremely rare item to theadvertisement server 115 capable of generating a great deal of online“buzz” and hence a greater level of exposure for the sponsor. Theadvertisement server 115 can auction off this rare item to a sponsor fora joint promotion. The loot server 125 may receive a portion of theproceeds for creating and promoting the rare item and offering the rareitem as part of the loot process.

Cross-platform metrics may be utilized by the loot server 125 to fosterloyalty and rewards systems and methods (including sponsorship andrewards) to create a more robust echo system to increase user engagementacross a wide variety of products and services and leverage online andsocial media “buzz” to maximize impact and minimize overall costs from aparticular marketing campaign. These techniques are particularlyapplicable to service providers who typically offer a wide range ofproducts and services. For example, where the service provider owns astadium or sports team, the loot server 125 may interface with theretail server 120 associated with the stadium and/or sports team(assuming user permissions) to monitor metrics such as ticketspurchased, how many times they play games associated with the team,promotions on social media, and time spent watching games and/orassociated programming. In this manner, the most loyal customers may berewarded appropriately using cross-platform metrics collected by lootserver 125.

Users who check in as a guest (e.g., without a registered account fromstep 704) are unlikely to obtain rare items or simply may be prohibitedfrom obtaining a rare item depending on the rule set and probabilitiesset in the loot server 125. Users who register with the loot server 125such as providing their e-mail and permissions to access certain loyaltyinformation, the users can boost their chances of obtaining a rare itemor other loot. If the user provides his or her Twitter, Discord,Instagram, Facebook, and/or other socials, then the user can obtain anadditional boost depending on the magnitude of their presence on socialmedia. The loot server 125 can give additional boosts for users which goon missions and/or demonstrate enhanced loyalty to the system. The lootserver 125 may provide added boost values depending on the number offollowers a user has and the extent to which the user promotes aparticular game, team, event, program, product, mobile service provider,and/or other service. The loot server 125 may, for example, weigh userswith a larger following more. The loot server 125 may, for example,leverage its cross-platform information to determine that a user has theservice providers mobile device, is at the service providers game,bought tickets through the service provider, and reward the customer forhis or her loyalty in unique ways in order to build brand loyalty.Further, service providers could interconnect various loot servers 125and advertisement servers 115 with other service provider's loot serversand advertising servers (not shown) to share loyalty rewards acrossplatforms such as XFINITY teaming with Verizon or other NHL teams tocross-promote certain products or services and share advertising revenueand potential loot. This can be done in an automated way to create arobust market place with national and international reach.

For example, the loot server 125 could arrange for a quest for dinner ora photo with one of the players and build out challenges and tasks(e.g., using Gaming server in the walled garden 119 and/or eSportsstreaming server 123) designed to give one or more users a quest. Thequest can be in the real world or the virtual world and any variation inbetween to keep the process interesting. Additional, a reality TV showcan track the quest of the real-life teams and promote the quests. Byvarying the design of the quests and loot process, the loot server 125can help keep the process interesting and maintain the buzz about theloot options.

Additionally, the loot server 125 may tie expensive buys such as a suiteat Comcast Center to specialized loot such as a signed jersey or maybe ajersey signed by the whole team. It may not happen with every purchase,but as the loyalty score increases and the price of the suite increases,the probability of receiving a rare item also increases based onexamples of the loot probability calculation in the loot server 125.

For video games, the loot may include virtual products in the video gamethat are unavailable otherwise such as a special gun or armor. Ingeneral, individuals and especially those who frequent social mediatypically are attracted to and work hard for things that are reallyunique and hence can become really valuable. The loot server 125 createsa market place for these unique and valuable items that can beauthenticated.

The loot server 125 may be paired with identification technology such asa near field communication device, RFID device, security chip and/orother portable authentication device that can be read by a readerincluding a cell phone with or without an inductive charger. Thatdatabase can be used and managed by the loot server in conjunction withthe retailer, network, sports team, service provider, etc. so that itemsmay be authenticated and transferred in the market place. The lootserver 125 may also charge an authentication fee and provide insuranceto ensure the items authenticity. The control and transfer of the itemscan be tracked using various technologies, including algorithms used byelectronic currency such as the SHA-256 algorithm used by Bitcoin. Inthis manner, the loot server 125 may organize the transfer andauthentication of rare items in the secondary market—increasing brandloyalty and the value of the rare items. Further, the team can trackownership and the really rare items or loot and super privileges, andhence determine additional loyal customers assuming they agree to enterinto the system. With proper authentication, the loot server 125 cancreate and support an entire submarket and demand for virtual as well asmerchandise products that are authenticated via technology (e.g., SHA256 hash algorithm) and hence make the loot even more valuable bysupercharging the secondary market for trading in those products. Thisprocess substantially increases brand loyalty and feeds back into therewards process and creates greater incentive to participate.

The loot server 125 allows individuals to invest in the loot because theloot may go up in value over time, especially if a player retires or ifthe loot is truly unique. Where you have a player's ultra-rare jerseyworn at a special game, then the value is going to skyrocket increase.

The loot server 125 over time can track of where their rarity items aregoing, how many are left in the world, and that can be used to createvalue and track value and to track from people who are all in on thegame. For example, the loot server 125 may boost their loyalty points ifthey collect X number of legendary items. Increasing their loyaltypoints will make their chances of getting additional legendary itemsincreased and hence build further brand loyalty.

The loot server 125 interacts with various other servers such as serversin the walled garden 119 and servers outside of the walled garden suchas servers 120-124. When a user logs into his account, and for examplebuys a hoodie, a transaction is made to the loot server 125 via anapplication program interface (API) to determine if the user is eligiblefor a rare hoodie. If the user is eligible for the rare hoodie, andpurchases the rare hoodie, the user can still return the hoodie if itdoes not fit and receive a different rare hoodie of a different size.The loot server 125 authentication, and loot registry 300, may beupdated after a returned item is received—a vendor may verify that thereturned item is indeed the one in the registry (e.g., by visualinspection, scanning a bar code or embedded RFID tag, etc.), and updatethe registry to indicate that the rare hoodie is in fact returned.Ideally, the user would be able to exchange a rare item for an item ofcomparable rarity (or even type, such as an exchange for differentcolors of the same rare hoodie) but if the user does not want anexchange, the user may be limited to receiving a nonrefundable credit,and the credit may be limited in its use. For example, the store creditmight only be used to purchase other items of the same rarity as thereturned hoodie. Such store credit might also be limited to purchasingitems of equal or lesser value than the exchanged item—this restrictionmay prevent users who may try to game the system by purchasing largequantities of low-cost items (e.g., socks) in order to get a good randomvalue for a rare item, and then trying to exchange that rare low-costitem for credit towards a rare high-cost item. So the loot server 125allows flexibility in cases where it doesn't fit but prohibits gamingthe system to up your rarity value.

A marketing team supports the loot server 125 with both advertisers andsocial media users to inform those involved of the availability of rareitems. For example, if fans are on social media for a sports team and arare jersey for the quarterback is being offered as loot, a lot of buzzthrough social channels may be created by letting the audience know ofthe availability of the jersey and how to increase the probability ofwinning the jersey. Winners would similarly be promoted. The goal wouldbe to sell more jerseys and hence help market the team, improve brandloyalty, and increase the overall buzz around the team during theoffseason.

The loot server 125 may promote certain products such as UniversalStudios Theme Park tickets that allow the individual to bypass any linesfor a year, meet the roller coaster designer, and/or go behind thescenes. Loyalty points (boosts) can be awarded through search history,past purchases, social media interactions, etc. The loot server 125 maybe used to identity rarity and the sponsor, coordinate theauthentication of the award in the third party market place and for thesponsor (e.g., Universal), facilitate the delivery and promotion of therarity on social media and the news media, and operate the ecosystem inan efficient transaction. Universal can advertise the availability ofthe “super ticket” via advertisement server 115 in the ecosystem too,for example, 50 million subscribers using the Canoe Ventures platform.After a user has won one of the super tickets, it may be authenticatedby the loot server 125, and then the winner can be promoted throughfurther advertisements. The process can be coordinated and authenticatedacross multiple hardware and/or software platforms making for a low costand efficient transaction.

The loot server 125 co-promote various entities for example, Universaland Nike who is coming on to the Canoe Ventures platform, and might saythey want to reach a gaming audience, people who play this game orfollow this esports team. They want to reach within this demographic andprovide a promotion of a super ticket or willing to fund the loot eitherindividually or collectively. The loot may be distributed based onloyalty points associated with the retailer whether that is Nike and/orUniversal, and may include additional tasks such as playing this game orwatching this Amazon TV series via streaming on an Xfinity platform,etc. For example, there may be a probability of winning Nike swag atyour next visit to Universal theme parks.

After an individual registers on the loot server 125, the individualaccrue anniversaries that give a higher boost. Further, more purchasesand additional loyalty may unlock additional functionality on thestorefront, so sometimes a user cannot see certain functionality untilthe user attains a certain level. This creates exclusivity andencourages people to reach a higher reward level—e.g., gold status. Theloot server 125 can maintain track of loyalty across multiple outlets(e.g., Budweiser and Universal) and across joint reward ventures. Inthis way, a user is not required to have hundreds of reward cards, but asingle account on the loot server 125. Loyalty points (boosts) may betracked and promoted separately and with options for cross-pollinationfor different loyalty programs, vendors, teams, and service providers.By tying the loot server 125 to social media interactions, the mostloyal customers that are promoting the service, have substantiallyincreased probabilities of obtaining rarer loot. The loot server 125probability system utilizes a variety of factors to maximize the buzzand provide transparency to explain rules and conditions for the lootrewards that the user may have received, and hence substantiallyincreases the value of the rewards program by weighting online andsocial media and gaming feedback. With cross-platform metrics, the lootserver can determine who's doing what online through deep packetinspection, tie that to individual users who have signed up through theloot server system to give permission to take a look at that data andthen reward them appropriately. The people who are out there that have amillion followers that are pitching a particular sports team, or game,or product or service get a much higher reward basis from the lootserver 125. By adjusting the probabilities to weight and categorizesocial media interactions as favorable and promotional, the loot server125 can increase loyalty and the reasons you should be tweeting aboutstuff or sharing things on Instagram to promote the product or service.

The loot server 125 creates a multiplicative impact to encourage socialmedia users to promote their team, an important game, a network, aservice provider, and/or other service. A user who has a large socialmedia following may have a much higher probability of being awardedrarity items associated with that product that they are helping topromote. With that positive feedback, people will try to get those rareitems, which may also create a secondary market to make those items moreprofitable. Thus, the loot server 125 using cross-platform metricscreates a new marketing technique and advertising echo system that ishighly integrated, efficient, and creates positive feedback to encouragefurther support and allow items to go viral.

Although examples are described above, features and/or steps of thoseexamples may be combined, divided, omitted, rearranged, revised, and/oraugmented in any desired manner. Various alterations, modifications, andimprovements will readily occur to those skilled in the art. Suchalterations, modifications, and improvements are intended to be part ofthis description, though not expressly stated herein, and are intendedto be within the spirit and scope of the disclosure. Accordingly, theforegoing description is by way of example only and is not limiting.

For example, the example above applied boost values to the user'sinitial probability value. Additionally or alternatively, boost valuesmay be applied to the table 400 itself. For example, a 3% increase tothe user's probability may be implemented as a 3% decrease in the listedprobabilities in table 400.

FIG. 9A illustrates an architectural level schematic of an exampleenvironment 900A of system 100 where certain details are abstracted. Theloot server 922 may be hosted in a cloud based system such as Amazon WebServices (AWS) and may be localized or distributed nationally orinternationally and may include load balancing to handle multiplerequests from large number of users. The environment 900 includes thenetwork(s) 902 (e.g., the Internet, service provider networks 903, 904,905, and 906 such as COMCAST, VERIZON, SPRINT, AT&T, T-MOBILE, STARLINK,GOOGLE FIBER, LAN, WAN, WiFi, wireless such as 5G and other networks),multiple social media platforms 910 (e.g., FACEBOOK, TWITTER, INSTAGRAM,LINKEDIN), retail platforms 912 (e.g., AMAZON, WALMART, BUDWEISER),gaming platforms 914 (e.g., OVERWATCH), content servers 916 (e.g., HBO,CNN, MSNBC, CBS, NBC, Netflix, AMAZON, APPLE, HULU), sport streamingplatforms 918 (e.g., NFL, MLB, NBA, NLH, MANCHESTER UNITED),advertisement recommendation systems/support 920 (e.g., COMCASTTECHNOLOGY SERVICES, GOOGLE AD MANAGER, FREEWHEEL, VUBIQUITY),advertisement agencies 930, and a loot server 921 hosting a loot system922. Users 954 may be connected to the loot server 921 through anysuitable mechanism such as the network 902. Users 954 may include one ormore individuals who utilize the functionality of the loot system 922hosted by the loot server 921. Users 954 can interact with the lootsystem 922 through many devices including in some examples the followingdevices: a smartphone, a personal computing (PC) device such as adesktop or laptop computer, a media center device or other PCderivative, portable media consumption device (mobile terminal, personaldigital assistant (PDA), gaming and/or media console, etc.), a tabletcomputer, television, gaming device, voice assistant, IOT device,consumer electronic device, or the like. In some examples, the devicesof the users 954 may include an application for interacting andcommunicating with the loot system 922. For the sake of the currentdiscussion, only five users are shown to be connected to the loot system922 through the network 902. However, any number of users can beconnected to the loot system 922 through the network 902. References tothe users 954 may include their devices.

Network(s) 902 couple the users 954, the multiple social media platforms910, the multiple retailers 912, the multiple gaming platforms 914, themultiple content servers 916, the multiple sport streaming platforms918, the multiple advertisement recommendation systems 920, theadvertisement agencies 930 and the loot server 921 hosting the lootsystem 922, all in communication with each other. The actualcommunication path through the network(s) 902 can be point-to-point,mesh, distributed, and span public and/or private networks, includingthe Internet.

The loot system 922 may interact with multiple social media platforms910 in order to monitor the behaviors of the users 954 of the lootsystem 922 on the social media platforms. The loot system may award rareloot items to the users 954 based on their behaviors on the social mediaplatforms 910. Examples of social media platforms include FACEBOOK,INSTAGRAM, OZONE, WEIBO, TWITTER, REDDIT, PINTEREST, TUMBLR, FLIKR,LINKEDIN, MEETUP, etc.

The loot system 922 may interact with multiple retail platforms 912 inorder to monitor the purchase histories of the users 954 of the lootsystem 922. The loot system may award rare loot items to the users 954based on their purchase histories and behaviors. Examples of retailplatforms include AMAZON, TARGET, WALMART, MACY'S, NFLSHOP.COM, NHL.COM,FANATICS.COM, etc.

The loot system 922 may interact with multiple gaming platforms 914 inorder to monitor the behaviors of the users 954 of the loot system 922in the gaming platforms 914. The loot system may award loot items to theusers 954 based on their behavior and winnings in the gaming platforms.Examples of gaming platforms include OVERWATCH, FORTNITE, LEAGUE OF THELEGENDS, WORLD OF WARCRAFT, LEAGUE OF THE LEGENDS, PALADINS, STAR WARSBATTLEFRONT, etc.

The loot system 922 may interact with multiple content servers 916. Thecontent servers 916 may be configured to provide content to the devicesof the users 954. The content servers may provide, for example, video,audio, text, web pages, images, files, and so on to the users 954. Thecontent servers 916 may be configured to broadcast live events tomassive audience, video on demand, recorded content, and/or broadcastpre-recorded content. The loot system 922 may monitor the viewinghistories and behaviors of the users 954 in the content servers 916either directly via deep packet inspection and/or machine learning-basedmodels. The loot system may award loot items to the users 954 based ontheir viewing behavior. Examples of content servers include NETFLIX,AMAZON PRIME, HULU, COMCAST, YOUTUBE, REDBOX, etc.

The loot system 922 may interact with one or more sport streamingplatforms 918. A sport streaming platform provides a way to broadcastlive sport competitions or video game competitions to the users 954. Themost common video game genres associated with video game competitionsare multiplayer online battle arena (MOBA), first-person shooter (FPS),fighting, digital collectible card games, battle royale games andreal-time strategy (RTS). Popular video games played in the video gamecompetitions include LEAGUE OF LEGENDS, DOTA 2 AND SMITE,COUNTER-STRIKE, CALL OF DUTY, CROSSFIRE, RAINBOW SIX SIEGE, OVERWATCH,STREET FIGHTER, SUPER SMASH BROS., MORTAL KOMBAT, SOULCALIBUR, etc.Examples of video game competitions include LEAGUE OF LEGENDS WORLDCHAMPIONSHIP, OVERWATCH LEAGUE, etc. Examples of sport streamingplatforms for video games include Twitch, YouTube Live Gaming,Dailymotion Games, Smashcast.tv. ESPN, TBS, etc. Examples of live sportcompetitions include sporting events from Major League Baseball (MLB),the National Basketball Association (NBA), the National Football League(NFL), and the National Hockey League (NHL), U.S. OPEN (GOLF), U.S. OPEN(TENNIS), DAYTONA 500, etc. Examples of sport streaming platforms forlive sports competition include StreamSports, WatchESPN, FuboTV,YouTube, etc.

The advertisement recommendation systems 920 may be configured toprovide advertisement services associated with loot items and lootscores awarded by the loot system 922. The advertisements recommended bythe advertisement recommendation systems 920 may be associated withand/or derived through the social media platforms 910, the retailplatforms 912, the gaming platforms 914, the content servers 916, thesport streaming platforms 918, advertising agencies 930, advertisingdata providers, and/or service providers hosting/utilizing variousnetworks 902. The advertisement recommendation systems 920 may store andprovide advertisement files to be presented to users 954 with audioand/or video (e.g., audiovisual) programs, Internet access, video games,etc. The advertisement recommendation systems 920 may be responsible forformatting and inserting advertisements in a video stream beingtransmitted to devices of the users 954. The advertisements may betargeted to users 954 and/or their devices based on various demographicinformation, content consumption history, purchase histories, behaviorin social media platforms, sports consumption history, devicecapabilities, and configurations, etc. Certain advertisements may onlybe available to users who have a certain loot score. For example, if theuser has received enough boosts, the user may be provided advertisementsfor certain unique or difficult to obtain items. Examples ofadvertisement recommendation systems include the Project Canoeinitiative including Comcast, Time Warner Cable, Cablevision, CoxCommunications, Charter Communications, and Bright House Networks,Google Ads, Quantifi Digital, etc.

Advertisement agencies 930 may handle advertising and promotion of lootscore and items for one or more retailers, gaming platforms, contentserver, service providers, and sports streaming platforms.

FIG. 9B illustrates an architectural level schematic of a second exampleenvironment 900B of system 100 where any of the multiple social mediaplatforms, retail platforms, gaming platforms 914, content servers 916,sports streaming platforms 918, advertisements recommendation systems921, and advertisement agencies 930 may be configured to host their ownloot server 921 comprising a loot system. Content sources 916, gamingplatforms 914, sports streaming platforms 918, retail platforms 912,social media platforms 910, and service providers 903-906 are allincreasing in number and sophistication. For example, users andadvertisers have a vast array and ever increasing choice of contentsources 916, gaming platforms 914, sports streaming platforms 918,retail platforms 912, social media platforms 910, and service providers903-906. The transaction costs for advertising agency to run a unifiedtarget advertising campaign across all of these various entities is everincreasing. Incorporating a loot server 921 in each of these entities(either directly or virtually e.g., in the cloud using services such asAmazon Web Services) reduces transaction costs for advertisers bycreating a seamless architecture to share 1) loot (e.g., unique, rare,or more rate items) that may be offered by one loot server 921 to otherloot servers 921 to use in an advertising campaign, 2) offers of classesof customers which may receive targeted advertisements (e.g., 500,000households with an income level over $50K that live in certain zipcodes), and offers of types of ad placement opportunities available(e.g., ads inserted in to various types of content such as VOD, games,social media and inserted in a particular fashion (video ads, staticads, product placements dynamically incorporated into scenes)), and/or3) requests to place ads by advertising agencies which may be respondedto within the loot ecosystem. In this way, an ad agency or a dealershipin N.J. may log onto a loot server and ad agencies for creating aadvertising campaign, service providers for distributing the advertisingcampaign, and content in which to place the advertising campaign inorder to reach the dealerships target audience. The transactions may allbe coordinated and facilitated via the loot server ecosystem using lootservers 921 working cooperatively to exchange secure anonymized datawhich protects the privacy of the target customers as well as thebusiness processes (e.g., price of an ad placement) of each of theentities in FIG. 9B including a loot server. The loot server ecosystemdescribed herein substantially reduces transaction costs for all partiesand allows advertisers to create and field advertising campaigns withsubstantially reduced transaction costs. As described herein, lootservers/systems from various platforms may communicate with each otherfor promoting merchandise and loot items and scores in a secure andanonymized manner to protect privacy.

FIG. 10 illustrates an example loot system 922, which may beimplemented, for example, on one or more a loot server(s) 921. The lootserver(s) 921 can be one or more computing device(s) such as the oneillustrated in FIG. 8 and may be implemented on a cloud service such asAmazon Web Services (AWS) and may also include load balancing. The lootsystem 922 can be implemented on the loot server(s) 921 as aSoftware-as-a-Service (SaaS) application, a web-architected applicationor a cloud-delivered service. The loot system 922 can be implemented inthe context of any computer-implemented system, including a databasesystem, a multi-tenant environment, or a relational databaseimplementation.

Referring to FIG. 10 , the loot system 922 may be variously configuredand may include software components such as an internal retail storeprocess 1030, a new user process 1050, a boost monitor process 1051, aloot ownership process 1052, an advertisement coordinator process 1054,an external purchase process 1056, a loot authenticator process 1062and/or a boost informer process 1058. The internal retail store 1030 mayinclude additional software components such as a new purchase process1032, a return process 1036, an exchange process 1032. The loot system922 may also include a users database 1002, an available commoninventory database 1004, an available loot inventory database 1008, aloot item ownership registry 1010, a purchase records database 1012, areturn records database 1014, an advertisement database 1018 and/or anexchange records database 1016. A database may comprise two or moreseparate databases, and when considered together, still constitute a“database” as that term is used herein and a database distributed acrossa cloud or the Internet may still be a “database.”

The internal retail store 1030 may offer a website for the sale ofmerchandise from the available common inventory database 1004 and theavailable loot inventory database 1008 to the users 954. The newpurchase process 1032 processes purchase of merchandise by the users 954of the loot system from the available common inventory database 1004 andapplies loot scores of the users 954 to bolster their chances ofobtaining rarer merchandise or loot items from the available lootinventory database 1008. The new purchase process 1032 records theprocessed purchases in the purchase records database 1012. The returnprocess 1036 processes returns of merchandises and records the returntransactions in the return records database 1014. The exchange process1034 processes exchanges of merchandises and records the exchangetransactions in the exchange records database 1016.

The new user process 1050 processes the registration of new users of theloot system 922. The loot ownership process 1052 processes changes inthe ownership of loot items in the loot item ownership registry process1010, and allows the users 954 to verify ownership to facilitate futuretransfers of the items. The loot ownership process 1052 allows users 954to record and track transfers of a loot item along with relevantauthentication data such as data associated with an embeddedauthentication tag in the item. The advertisement coordinator process1054 interacts with the advertisement recommendation systems 920 forproviding advertisement services associated with loot items and lootscores awarded by the loot system 922. The external purchase process1056 coordinates the application of loot scores during the purchase ofmerchandise by the users 954 from the retail platforms 912 outside theloot server 921. The application of the loot scores bolsters the users'chances of obtaining rarer merchandise or loot items. The boost informerprocess 1058 informs the users 954 of available loot scores and upcomingchances for winning loot scores and loot items. The boost monitorprocess 1051 monitors the behavior of the users 954 of the loot system922 across multiple platforms, such as the social media platforms 910,the retail platforms 912, the gaming platforms 914, the content servers916, and the sport streaming platforms 918.

The loot authenticator process 1062 processes the authentication of lootitems. Each loot item can be paired with identification technology suchas a near field communication device, RFID device, and/or security chip.The loot item ownership registry 1010 may be configured as a databaseand may be used to track ownership of the loot items in conjunction withthe retail platforms 912.

The loot server 922 may also include a task scheduler process 1060. Thetask scheduler process 1060 may be variously configured such as toschedule various tasks in the loot system 922, such as requesting theboost monitor process 1051 to monitor the behavior of the users 954 ofthe loot system 922 across multiple platforms, such as the social mediaplatforms 910, the retail platforms 912, the gaming platforms 914, thecontent servers 916, the network(s) 902 and the sport streamingplatforms 918. The boost monitor process 1051 may request the boostinformer process 1058 to inform the users 954 of available boosts andupcoming chances for winning boosts. This feedback provides an addedincentive for the users and encourages the users to maximize activitiesthat will boost their probabilities.

FIG. 11 illustrates an example boost monitor process 1051. The boostmonitor process 1051 may include software components referred to hereinas a location monitor process 1102 for monitoring a user's location, alive match monitor process 1104 for monitoring a user's location and/oractivities during a live match, a gaming platform monitor process 1106for monitoring a user's interaction with various games, game relatedactivities, and/or gaming platforms, a purchase monitor process 1108 formonitoring a user's purchase activities, a social media monitor process1110 for monitoring a user's interaction with social media, a contentserver monitor process 1112 for monitoring a user's interaction withcontent, a photo monitor process 1112 for monitoring a user'sinteraction with various photo content, a calendar monitor process 116for monitoring a user's interaction with calendars, and/or a healthmonitor process 1118 for monitoring a user's interaction with healthrelated application such as an Apple Watch or Fitbit. These processesmay comprise one or more processes co-hosted on a single server and/ordistributed across multiple computer platforms. These may be selectivelyenabled or disabled by a user participating in the boost program topreserve a user's privacy. The boost monitor process 1051 also includesa user loot scores database 1120 and a loot boost rules database 1126.The loot boost rules database 1126 may comprise a table, such as theboost table 600 in FIG. 6 and the loot boost rules database 1126 mayinclude rules (e.g., as described elsewhere herein) as to how to boost auser's probabilities based on user's activities.

FIG. 12A shows an example of the users database 1002 in FIG. 10 . Theusers database 1002 may be configured, for example, to containinformation regarding the registered users of the loot system 922. Theusers database 1002 may include, for example, a unique user ID 1202 foreach user and/or various identifying information about the user such asthe name of the user 1004. The users database 1002 may be configured toinclude, for example, one or more email address(s) 1206 and/or one ormore phone number(s) 1208 of the users. The users database 1002 may alsoinclude, for example, account ID and/or login credentials for variousaccounts the user may have across multiple platforms, such as the socialmedia platforms 910, the retail platforms 912, the gaming platforms 914,the content servers 916, and/or the sport streaming platforms 918. Forexample, the user may be provided an option to opt in for trackingvarious activities to allow for increased boost loot probabilities. Theusers database 1002 may include account ID and/or login credentials forthe social media A 1210, the social media B 1212, the esports platform A1214, the gaming platform 1216, and the content server 1218. As shown inFIG. 12A, an example entry in the users database 1002 includes the userJohn Smith with the user ID 1001, the email address jsmith@gmail.com,the phone number 438-729-7214, jsmithy as ID for the social media A,JohnSmith as the ID for the social media B, BugsBuggy as the ID for theesports platform A, Pluto as the ID for the gaming Platform A and jsmithas the ID for the content server A. Columns for only two social mediaplatforms, one sports platform, one gaming platform and one contentserver are shown in the users database 1002 in FIG. 12A. However,account ID and login credentials for any number of social mediaplatforms, sport streaming platforms, gaming platforms, retailplatforms, networks, and/or content servers can be included in the usersdatabase 1002. The users database 1002 may also include other optionaluser information 1220 that might be helpful for the functionality of theloot system 922, e.g., the password for the user account, the timestampof last sign in, the timestamp for user account creation, userorganization, profile picture, time and dates of activities that boostedor reduced the loot probabilities, and/or other items such as thosediscussed herein.

FIG. 12B shows an example of the available common inventory database1004 in FIG. 10 . Merchandise or items listed in the available commoninventory database 1004 may or may not be considered a loot item. Foreach type of item available for purchase in the loot system 922, theavailable common inventory database 1004 may include an item ID or astock keeping unit (SKU) ID 1222, an item description 1224, a loot class1230 indicating that the item is “common”, the price 1232 and number ofitems available 1234. For clothing items, the available common inventorydatabase 1004 may also include a size 1226 and color 1228 of the item.The available common inventory database 1004 may also include otheroptional information 1238 that might be helpful for the functionality ofthe loot system 922, e.g., the name and contact information of thesupplier of the item, the timestamp of last order, the order number, andso on.

FIG. 12C shows an example of the available loot inventory database 1008in FIG. 10 . Merchandise or items listed in the available loot inventorydatabase 1008 may be considered a loot item or a rare item. For eachtype of loot item available in the loot system 922, the available lootinventory database 1008 may include a stock keeping unit (SKU) ID 1240,an item description 1242, a loot class 1248, the price 1250 and numberof loot items available 1252 for the loot type. For clothing items, theavailable loot inventory database 1008 may also include a size 1244 andcolor 1246 of the loot item. The loot class 1248 may indicate the rarityof the loot item (e.g., Good, Rare, Superior, Epic, Legendary). Theavailable loot inventory database 1008 may also include other optionalinformation 1254 that might be helpful for the functionality of the lootsystem 922, e.g., the name and contact information of the supplier ofthe loot item, the timestamp of last order, the order number, and/orother information as discussed herein.

FIG. 12D shows an example of the loot item ownership registry database1010 in FIG. 10 . The loot item ownership registry database 1010 maytrack the ownership of loot items, and track transfers of the loot itemalong with relevant authentication data such as data associated with anembedded authentication tag which may be included in the item. For eachloot item, the loot item ownership registry database 1010 may include anitem ID 1260, an item description 1262, a loot class 1268, the name 1276of the owner of the loot item, the user ID 1274 of the owner, thestating date 1270 of ownership, the end date 1272 of ownership and/orcredentials for the authentication tags 1278 embedded in the loot item.For clothing items, the loot item ownership registry database 1010 mayalso include a size 1264 and/or color 1266 of the loot item. The lootclass 1268 may indicate the rarity of the loot item (e.g., Good, Rare,Superior, Epic, Legendary). For example, the loot item ownershipregistry database 1010 may include ownership record of the loot itemwith item ID 23516b from Mar. 4, 2019 to Aug. 1, 2019. From Mar. 1, 2019to May 2, 2019, the loot item with item ID 23516b was owned by BobSmith. Alice Jones owned the loot item with item ID 23516b from May 2,2019 to Jul. 1, 2019. Chad Davis owned the loot item from Jul. 1, 2019to Jul. 5, 2019. Deadshot_Dale owned the loot item from Jul. 5, 2019 toAug. 1, 2019. An owner with the email ID 51324 @email.com currently ownsthe loot item with item ID 23516b. The loot item ownership registrydatabase 1010 may also include other optional information 1280 thatmight be helpful for the functionality of the loot system 922, e.g., themailing address and phone numbers of the owners and/or a one way hashcode that can generate a new hash code or blockchain cipher code valuefor printing on a certificate to pass on to a purchaser to authenticatethe loot item.

FIG. 12E shows an example of the user loot score database 1120 in FIG.11 . The user loot score database 1120 records unused and unexpired lootscores for the users 954 of the loot system 922. The user loot scoredatabase 1120 includes a loot score 1284, the user ID 1982 of the userassociated with the loot score, and an expiry date 1286 for the lootscore. In some examples of the loot system 922, loot scores may notexpire and may be available for use till the users associated with theloot scores use them during purchase of merchandise. In some examples ofthe loot system 922, there may be one entry for a user of the lootsystem in the user loot score database 1120 indicating a total lootscore available for the user. In some examples of the loot system 922,there may be multiple entries for a user of the loot system in the userloot score database 1120, and the total loot score available for theuser can be determined by summing the loot scores of the multipleentries. In some examples of the loot system 922, the loot server mayremove entries with loot scores that are past their expiry dates. Theuser loot score database 1120 may also include other optionalinformation that might be helpful for the functionality of the lootsystem 922.

FIG. 12F shows an example of the loot/boost rules database 1126 in FIG.11 . The user loot score database 1120 records boosts/loot scoresassociated with various advertisement campaigns that may be initiated byany one of the multiple social media platforms, retail platforms, gamingplatforms, content servers, sports streaming platforms, advertisementsrecommendation systems, and advertisement agencies or by the lootsystem. The boosts/loot scores database 1126 may include informationregarding the advertisement campaign 1291, a name for a boost 1292associated with the advertisement campaign, the loot score 1293 andrules 1294 associated with the boost. For example, an advertisementcampaign for retailer A indicates that 0.5% boost may be awarded to auser if the user purchases at least five items from retailer A in oneday. Some boosts may comprise multiple rules. The boosts/loot scoresdatabase 1126 may also include other optional information that may beuseful for the functionality of the loot system 922, such as an expirydate for the boost and/or an expiry date for all boosts from anadvertisement campaign. For example, as the user's active participationbecomes older in time, the boost provided to that user eventually beginsto decrease. This may also trigger processes within the loot system 922to reengage the user and encourage the user to reengage such asproviding a promotion of a unique or rare loot item believed to be ofinterest to the user.

FIG. 13 is an example workflow 1300 illustrating a representative methodof processing a new user 1302 in the loot system 922. The actions in theworkflow 1300 may be performed in different orders and with different,fewer, or additional actions than those illustrated in FIG. 13 .Multiple actions can be combined in some implementations.

FIG. 13 includes an example workflow 1300 that begins at step S13.1where a new user 1302 may sign up as a user in the loot system 922.Workflow 1300 continues at step S13.2 where the new user process 1050may add information about the user 1302 to the users database 1002. Atstep S13.3, the new user 1302 may provide information about his/heraccount (e.g., user ID and login credentials) in the social mediaplatform A to the new user process 1050. At step S13.4, the new user1302 may provide information about his/her account (e.g., user ID andlogin credentials) in the social media platform B to the new userprocess 1050. At step S13.5, the new user 1302 may provide informationabout his/her account (e.g., user ID and login credentials) in the sportstreaming platform A to the new user process 1050. At step S13.6, thenew user 1302 may provide information about his/her account (e.g., userID and login credentials) in the gaming platform A to the new userprocess 1050. At step S13.7, the new user 1302 provides informationabout his/her account (e.g., user ID and login credentials) in thecontent server A to the new user process 1050. At step S13.8, the newuser process 1050 may add information regarding the new user 1302accounts in the social media platform A, the social media platform B,the sport streaming platform A, the gaming platform A, and the contentserver A in the users database 1002. The new user 1302 may provideinformation about his/or account in more social media platforms, sportstreaming platforms, gaming platforms, and content servers to the newuser process 1050. While the processes in FIG. 13 have been described interms of user input, this information may also be obtained via securedexchange with the various platforms, for example, once the user grantspermissions the exchange of data may occur automatically.

FIG. 14A is an example workflow 1400 illustrating a representativemethod of monitoring the location of a user 1402 by the location monitor1102 in the boost monitor 1051 in the loot system 922. This may be donevia GPS enabled devices such as phones, watches, or tablets, viatriangulation or distance and bearing in the case of wireless devices,MAC and/or IP address location techniques. The workflow 1400 begins atstep S14.1 where the location monitor 1102 may retrieve informationregarding a personal device (e.g., a phone number) of the user 1302with, for example, location sensing capabilities from the users database1002. The personal devices with location sensing capabilities canestimate their locations through beacons (e.g., IBEACONS and SENIONbeacons), communications with one more GPS satellites, proximity to oneor more WiFi sources, multilateration of radio signals between severalnearby cell towers, IP addresses of the personal devices, and so on. Atstep S14.2, the location monitor 1102 may determine the location of theuser 1402 by determining the location of the personal device of the user1402. The personal device of the user 1402 may send the geospatialcoordinates of the location (e.g., the latitude and the longitude)and/or other location indicating information including physical address,zip code, and/or approximate address.

At step S14.3, the location monitor 1102 may determine if the locationof the user 1402 is within a place-of-interest such as a place ofinterest as determined by the loot/boost rules database 1126, such asthe Phillips Arena 1442 in FIG. 14B, or within a certain distance orboundary of a place-of-interest, such as boundary 1444 of the PhillipsArena 1442. A place-of-interest may be a specific location that someonemay find useful or interesting or it may be specified in the loot/boostrules database 1126. In some examples of the loot server 922, thelocation monitor 1102 and/or rules database can include a database ofplaces-of-interests. The database of point of interests may includeplaces-of-interests from one or more places-of-interests sources, suchas Google Map, Bing Maps, Apple Maps, MapQuest, Roadtrippers, and/or asspecified by one or more advertisers. The loot server 922 may include alocation monitor 1102 that may interact with one or more of the aboveplaces-of-interest sources to determine if the location of the user 1402is within a place-of-interest. After determining if the location of theuser 1402 is within a place-of-interest or within the boundary of theplace-of-interest, the location monitor 1102 may determine whether thelocation of the user 1402 qualify for a loot score based on theloot/boost rules in the loot/boost rules database 1126 in the boostmonitor 1051. For example, rules in the loot/boost rules database 1126may indicate that the location 1422 inside the Phillips Arena 1442 orwithin the boundary 1444 of the Phillips Arena qualify for a loot scoreof 1%. However, the location 1424 outside the Phillips Arena 1442 do notqualify for a loot score.

At step S14.4, the location monitor 1102 may award the loot score to theuser 1402 if the location of the user 1402 qualify for a loot score. Theloot score awarded to the user 1402 may be recorded in the user lootscores database 1120. At step S14.5, the location monitor 1102 maynotify the user 1402 of the awarded loot score. The notification may besent through an email, a text message, or a notification through anapplication communicating with the loot system 922 in the personaldevice of the user 1402. This may increase the user feedback and provideadded incentive for the user to engage in activities that are beingencourage, and that may result in an increase in his/her loot scores.

FIG. 15 is an example workflow 1500 illustrating a representative methodof monitoring a live game event by the live match monitor 1103 in theboost monitor 1051. The workflow 1500 begins at step S15.1 where thelive match monitor 1104 may receive one or more of a live video streamfrom the sport streaming platform A 1502 and monitors the video streams,the players in the video streams and/or the viewers of the live match.

The live match monitor 1104 may analyze and learn the behavior ofvarious objects (e.g., players, sporting objects such as a ball, a bat,etc.) in the video frames of the video streams by using any suitabletechnique such as machine learning-based models. The video stream may beformatted using known such formats, e.g., MPEG2, MJPEG, MPEG4, H.263,H.264, and the like. Examples of machine learning-based models includeregression-based models, neural network-based models, and/orfully-connected network-based models. Objects depicted in the videostreams by the machine learning-based models may be determined based onan analysis of the video frames. Each object may have a correspondingsearch model, which may be used to track objects motions frame-to-frame.The machine learning-based models may be configured to determine theclasses of the objects and generate semantic representations of theobjects. For example, in a live game event of a soccer match, themachine learning-based models may be able to identify the variousplayers, the ball and the goal posts. The machine learning-based modelsmay also be able to identify specific events or behaviors in the videostreams, such as a certain player scoring a goal. Streamsage classifiesevents in certain video streams using various techniques. Thesetechniques may be used to determine various events in the game that maygive a boost to a loot score if a purchase and/or other activity is madeclose in time to the event.

At step S15.2, the live match monitor 1104 may compare the users in theuser's database 1002 and the viewers of the live match in order todetermine a list of users of the loot system 922 that are watching thelive match. At step S15.3, the live match monitor 1104 may determinewhether watching the live match qualify for a loot score based on theloot/boost rules in the loot/boost rules database 1126 in the boostmonitor 1051. In some examples, the users watching the live match mayqualify for a loot score after watching the live match for a minimumamount of time. At step S15.4, the live match monitor 1104 may award theloot score to users watching the live match if watching the live matchqualify for a loot score. The loot scores awarded to the users may berecorded in the user loot scores database 1120. The live match monitor1104 may notify the users viewing the live match of the awarded lootscores. The notification may be sent through an email, a text message,or a notification through an application communicating with the lootsystem 922 in the personal devices of the users.

At step S15.5, the live match monitor 1104 may determine if any gameevents in the live match qualify for a loot score. For example, a lootscore of 2% may be awarded to all viewers if the soccer player Messiscores a goal in a soccer match. At step S15.6, the live match monitor1104 may award the loot score to users watching the live match if thegame event in step S15.4 qualify for a loot score. Any loot scoresawarded to the users may be recorded in the user loot scores database1120. The live match monitor 1104 may notify the users viewing the livematch of the awarded loot score. The notification may be sent through anemail, a text message, or a notification through an applicationcommunicating with the loot system 922 in the personal device of theusers.

FIG. 16 is an example workflow 1600 illustrating a representative methodof monitoring video games played in a gaming platform A 1602 by theusers of the loot system. The gaming behavior and histories of the usersmay be monitored by the gaming platform monitor 1106 in the boostmonitor 1051. The workflow 1600 begins at step S16.1 where the gamingplatform monitor 1106 may select a user and retrieves informationregarding an account ID and/or login credentials of the user in thegaming platform A 1602 from the users database 1002. At step S16.2, thegaming platform monitor 1106 may determine the gaming behavior and/orevents of the selected user. The gaming behavior of the user mayindicate the amount of time that user spends in the gaming platform, theuser's interaction with other players in the gaming platform A, andother related behaviors. Game events of the user may indicate thewinning and/or the success level of the users while playing video gamesin the gaming platform. Examples of gaming events include the userreaching a certain stage/level in the game, winning awards, and/orachieving a milestone.

At step S16.3, the gaming platform monitor 1106 may analyze the behaviorof the user and his/her significant gaming events to determine whetherthe user qualifies for loot scores. For example, a loot score of 0.1%may be awarded to the user if the user plays video games in the gamingplatform A for two hours a day, or a loot score of 1% may be awarded tothe user if the user plays video games in the gaming platform A for fivedays in a row. Loot scores may also be awarded to the user forsignificant gaming events, such as winning five games in row and/orattaining certain levels in a game. The gaming platform monitor 1106 mayuse machine learning-based models to determine whether the userqualifies for loot scores.

At step S16.4, the gaming platform monitor 1106 may award loot scores tothe users if the gaming behavior and/or significant game events of theuser qualify for loot scores. The loot scores awarded to the user may berecorded in the user loot scores database 1120. The gaming platformmonitor 1106 may notify the user of the awarded loot score. Thenotification may be sent through an email, a text message, or anotification through an application communicating with the loot system922 in the personal device of the users.

FIG. 17 is an example workflow 1700 illustrating a representative methodof monitoring purchase histories of users by the purchase monitor 1108in the boost monitor 1051. The workflow 1700 begins at step S17.1 wherethe purchase monitor 1108 may select a user and may retrieve informationregarding account IDs and/or login credentials of the user from theusers database 1002 for online accounts in one or more retail platforms912. At step S17.2, the purchase monitor 1108 may determine the purchasehistory of the selected user from the retail platforms 912. The purchasebehavior of the user may indicate the amount the user spends inpurchasing merchandise, items bought, and so on. At step S17.2, thepurchase monitor 1108 may determine the purchase history of the selecteduser from the internal retail store 1030 from the purchase recordsdatabase 1012.

At step S17.3, the purchase monitor 1108 may analyze the purchasebehavior of the user to determine whether the user qualifies for lootscores. For example, a loot score of 0.5% may be awarded to the user ifthe user buys $500 worth of merchandise from Amazon.com, or a loot scoreof 1% may be awarded to the user if the user bought seasons tickets forLos Angeles Lakers from Ticketmaster.com. The purchase monitor 1108 mayuse using machine learning-based models to determine whether the userqualifies for loot scores.

At step S17.4, the purchase monitor 1108 may award the loot scores tothe users if the purchase behavior of the users qualifies for lootscores. The loot scores awarded to the user may be recorded in the userloot scores database 1120. The gaming platform monitor 1106 may notifythe users of the awarded loot scores. The notification may be sentthrough an email, a text message, or a notification through anapplication communicating with the loot system 922 in the personaldevice of the users.

FIG. 18A is an example workflow 1800 illustrating a representativemethod of monitoring social media accounts of a user by the social mediamonitor 1110 in the boost monitor 1051. The workflow 1800 begins at stepS18.1 where the social media monitor 1110 may select a user andretrieves information regarding account IDs and login credentials of theuser from the users database 1002 for the social media platform A 1802.

At step S18.2, the social media monitor 1110 may analyze posted picturesand videos in the social media platform A 1802 to determine items andpatterns that qualify for loot scores by using machine learning-basedmodels. Examples of machine learning-based models includeregression-based models, neural network-based models, and/orfully-connected network-based models. Items and patterns depicted in theposted photos and/or videos by the machine learning-based models aredetermined based on an analysis of the pixel frames in the images. Therecognition of a pattern, logo, and text in the images may be done bydissecting the image or videos into pieces to find features or objects.For example, the machine learning-based models may analyze the photo1842 in FIG. 18B posted the user John Smith of himself wearing asweatshirt in the social media platform A 1802 to detect the logo 1844for a sports team.

At step S18.3, the social media monitor 1110 may determine whether thedetected item, such as the logo 1842, qualify for loot scores. Forexample, a loot score of 0.5% may be awarded to the user if the logo isfor Philadelphia Fusion. At step S18.4, the social media monitor 1110may award the loot score to the users if the detected items qualify forloot scores. The loot score awarded to the user may be recorded in theuser loot scores database 1120.

At step S18.5, the social media monitor 1110 may analyze text 1846posted by the user in the social media platform A 1802 to determinephrases in the text that qualify for loot scores. The social mediamonitor 1110 may apply a heuristics-based string analysis to the text todetect phrases. The heuristics-based analysis may extract brand keyterms in the texts and detect associated brand labels based on theextracted brand key terms based on a set of learned rules. For example,the heuristic based analysis may identify the brand key term 1848“Philadelphia Fusion” in the text “Check out my awesome PhiladelphiaFusion sweatshirt” and associate the brand key term with the sports teamPhiladelphia Fusion. In some embodiments, the heuristics-based stringanalysis may include comparing phrases in the text to known aliases ofthe recognized brands. The heuristics-based analysis may also extractpositive key terms in the text, such as the phrase “awesome” in the text1846. Other possible positive key terms may include “good,” “best,”“loving it,” “like,” and so on. The heuristics-based analysis may alsoextract negative key terms in the text, such as the phrases “hate,”“dislike,” “not good,” “sucks,” and so on.

At step S18.6, the social media monitor 1110 may determine whether thedetected phrases, such as the phrase 1848, qualify for loot scores. Forexample, a loot score of 0.5% may be awarded to the user if the textposted includes the brand key term “Philadelphia Fusion.” In someexamples, the loot score may be awarded only if the positive key termsare also included with the brand key terms in the posted texts. Lootscored may not be awarded if negative key terms are detected in thetexts, such as the negative key term “hate” in the text “I hate thisPhiladelphia Fusion sweatshirt! ! ! !”. In some circumstances, lootscores may be deducted for certain unfavorable circumstances. At stepS18.7, the social media monitor 1110 may award the loot score to theusers if the detected phrases qualify for loot scores. The loot scoreawarded to the user may be recorded in the user loot scores database1120. The social media monitor 1110 may notify the user of the awardedloot score. The notification may be sent through an email, a textmessage, or a notification through an application communicating with theloot system 922 in the personal device of the users.

FIG. 19 is an example workflow 1900 illustrating a representative methodof monitoring content viewing histories of users by the content servermonitor 1112 in the boost monitor 1051. The workflow 1900 begins at stepS19.1 where the content server monitor 1112 may select a user andretrieves information regarding account IDs and login credentials of theuser from the users database 1002 for an account in the content server A1902. At step S19.2, the content server monitor 1112 may determine theviewing history of the selected user from the content server A 1902. Theviewing behavior of the user may indicate the amount of time the userspends in viewing content from the content server A 1902, shows andmovies watched, number of episodes watches in a show and so on.

At step S19.3, the content server monitor 1112 may analyze the viewingbehavior of the user to determine whether the user qualify for lootscores. For example, a loot score of 0.5% may be awarded to the user ifthe user watches ten episodes of Star Wars Rebels within a time period,and/or a loot score of 1% may be awarded to the user if the user watchesan entire season of Game of Thrones in one week. The content servermonitor 1112 may use using machine learning-based models to determinewhether the user qualify for loot scores.

At step S19.4, the content server monitor 1112 may award the loot scoreto the users if the viewing behavior of the user qualify for lootscores. The loot scores awarded to the user may be recorded in the userloot scores database 1120. The content server monitor 1112 may notifythe user of the awarded loot score. The notification may be sent throughan email, a text message, and/or a notification through an applicationcommunicating with the loot system 922 in the personal device of theusers.

FIG. 20 is an example workflow 2000 illustrating a representative methodof monitoring uploaded photos of recent purchases of a user by the photomonitor 1112 in the boost monitor 1051. The workflow 2000 begins at stepS20.1 where the photo monitor 1112 may select a user and retrievesinformation regarding account IDs and/or login credentials of theselected user from the users database 1002 for online accounts in one ormore retail platforms 912. At step S20.2, the photo monitor 1112 mayanalyze posted pictures and videos on the retail platforms 912 platformto determine items and/or patterns qualify for loot scores by usingmachine learning-based models described herein. At step S20.3, the photomonitor 1112 may analyze posted pictures and videos from the internalretail store 1030 from the purchase records database 1012 to, forexample, determine items, and patterns qualify for loot scores.

At step S20.4, the photo monitor 1112 may determine whether the detecteditems in the uploaded photos in the retail platforms platform and/or theinternal retail store qualify for loot scores. At step S20.5, the photomonitor 1112 may award the loot scores to the user if items and objectsin the uploaded photos qualify for loot scores. The loot scores awardedto the user may be recorded in the user loot scores database 1120.

FIG. 21 is an example workflow 2100 illustrating a representative methodof monitoring health goals achieved by a user 2102 by the health monitor1118 in the boost monitor 1051. The workflow 2100 begins at step S21.1where the health monitor 1118 retrieves information regarding a personaldevice (e.g., a phone number) of the user 2102. The personal device ofthe user may include applications that track health goals of the user.Examples of such applications include Fitbit, MyFitnessPal, MapMyRun,MapMyFitness and so on. Examples health goals may include drinking tenglasses of water per day, running a marathon, working out five days aweek, and so on. At step S21.2, the health monitor 1118 checks thehealth applications installed in the user's personal device for recentachieved health goals. At step S21.3, the health monitor 1118 maydetermine whether any of the recent health goals achieved by the user2102 qualify for a loot score based on the loot/boost rules in theloot/boost rules database 1126. For example, rules in the loot/boostrules database 1126 may indicate that the running a marathon qualify fora loot score of 1%. At step S21.4, the health monitor 1118 may award theloot score to the user 2102 if any of the recent health goals qualifyfor a loot score. The loot score awarded to the user 1402 may berecorded in the user loot scores database 1120. In this example of theloot system, an athletic company may have some legendary swag that theycan award to the “biggest loser” of weight over a predetermined periodbased on the boost rules outlined herein. This may create substantialbuzz around the application, the athletic company, and motivate positiveactivities on the part of users.

FIG. 22 is an example workflow 2200 illustrating a representative methodof monitoring calendar events by the calendar monitor 1116 in the boostmonitor 1051. The workflow 2100 starts at step S22.1 where the calendarmonitor 1116 checks whether any of the recent events qualify for a lootscore based on the loot/boost rules in the loot/boost rules database1126. For example, rules in the loot/boost rules database 1126 mayindicate that all users of the loot system 922 qualify for a loot scoreof 1% during Thanksgiving day and that all users qualify for a lootscore of 0.5% during the Super Bowl game. At step S21.2, the calendarmonitor 1116 may award the loot scores to the users if any of the recentevents qualify for a loot score. For example, if the user attends theSuper Bowl game, he/she may be awarded additional loot scores. The lootscores awarded to the users may be recorded in the user loot scoresdatabase 1120.

FIG. 23A is an example workflow 2300 illustrating a representativemethod of informing users of available loot scores by the boost informer1058 in the loot system 922. The workflow 2300 starts at step S23.1where the boost informer 1058 retrieves information regarding a personaldevice (e.g., a phone number) of a user 2302 from the users database1002. At step S23.2, the boost informer 1058 checks the user loot scoresdatabase 1120 for total unexpired loot scores available to the user. Atstep S23.3, the boost informer 1058 notifies the user of the totalunexpired loot score. The notification may be sent through an email, atext message, and/or a notification through an application communicatingwith the loot system 922 in the personal device of the users. FIG. 23Bshows an example notification 2342 sent to a user's personal device 2340about available, unexpired loot scores. At step S23.4, the boostinformer 1058 checks the user loot scores database 1120 for loot scoresthat may be about to expire for the selected user. At step S23.5, theboost informer 1058 may notify the user of the loot scores that areabout to expire. FIG. 23B shows an example notification 2344 about lootscores about to the expired sent to the user's personal device 2340.

FIG. 24A is an example workflow 2400A illustrating a representativemethod of setting up an advertisement campaign by the advertisementcoordinator process 1054 for a platform A 2402. The platform A 2402 maybe a social media platform, a retailer, a gaming platform, a contentserver, a sports streaming platform, an advertisement recommendationsystem, or an advertisement agency. The advertisement campaign maycomprise targeted advertisements for upcoming chances to win boosts andloot items. At step S24.1A of the workflow 2400A, the platform A maysend information for an advertisement campaign to the advertisementcoordinator process 1054. The advertisement campaign may compriseboosts/loot scores for the campaign and advertisements associated withthe boosts/loot scores. At step S24.2B, the advertisement coordinator1054 may record the received advertisements in the advertisementsdatabase 1018 and record the received boost/loot scores in theloot/boost rules database 1126 at step S24.3.

FIG. 24B is an example workflow 2400B illustrating a representativemethod of sending targeted advertisements for upcoming chances to winboosts. The loot system 922 promote upcoming chances to win loot scoresvia direct advertisements to the users, and/or joint promotional withthe retail platforms 912. At step S24.1B of the workflow 2400, theadvertisement coordinator 1054 may be configured to track brand loyaltyof users across multiple platforms including the social media platforms910, the retail platforms 912, the gaming platforms 914, the contentservers 916, and the sport streaming platforms 918. At step S24.2B, theadvertisement coordinator 1054 may then transmit targeted advertisementsto users of a certain demographic based on the data collected at stepS24.1. At step S24.3B, the advertisement coordinator 1054 may alsointeract with the advertisement recommendation systems 920 for providingtargeted advertisements to the users of the loot system 922. At step24.4B, the advertisement recommendation systems 920 may transmittargeted advertisements to users of a certain demography. The users maybe provided with options to opt out of targeted advertisements, andother measures may be taken to protect user's privacy.

FIG. 24C is an example workflow 2400C illustrating a representativemethod of setting up an advertisement campaign in platform B 2464 byplatform A 2460. The platform A 2460 and/or the platform B may host aloot server comprising a loot system. The platform A and/or platform Bmay be a social media platform, a retailer, a gaming platform, a contentserver, a sports streaming platform, an advertisement recommendationsystem or an advertisement agency. The advertisement campaign maycomprise targeted advertisements for upcoming chances to win boosts andloot items. At step S24.1C of the workflow 2400A, the platform A 2460may send information for an advertisement campaign to the platform B2464. The advertisement campaign may comprise boosts/loot scores for thecampaign and advertisements associated with the boosts/loot scores. Atstep S24.2C, the platform B 2464 may transmit targeted advertisements tousers of a certain demography. The users may be provided with options toopt out of targeted advertisements, and other measures may be taken toprotect user's privacy.

FIG. 25 is an example workflow 2500 that illustrates a representativemethod of receiving a loot item during purchase of a common item from aninternal retail store 1030 of the loot system 922. The workflow 2500starts at step S25.1 where the new purchase process 1032 in the internalretail store 1030 receives an indication from a user 2502 to acquire anitem. For example, the indication may be sent to the new purchaseprocess 1058 if the user selects the checkout button 203 in FIG. 2B inan online purchase, and/or if the user otherwise acquires a new itemfrom the available common loot inventory database 1004. The acquisitionmay be described above as a purchase, but it need not be a purchase. Anytype of acquisition, such as a free gift and/or other reward, mayqualify for a chance at an item variant.

At step S25.2, the new purchase process 1058 may determine the unexpiredloot scores for the user 2502 from the user loot score database 1120.There may be one entry for the user 2502 in the user loot score database1120 indicating a total loot score available for the user, or there maybe multiple entries in the user loot score database 1120, and the totalloot score available for the user 2502 may be determined by summing theloot scores of the multiple entries.

At step S25.2, the new purchase process 1032 may determine if the user2592 may be eligible for a loot item in the available loot inventorydatabase 1008 based on the unexpired loot scores of the user. Asdescribed in step 707 of FIG. 7A, an initial probability value may bedetermined for the user's purchase transaction by the new purchaseprocess 1032. The initial probability value may be a random valuebetween 00.0 and 100.0. These values may be merely examples, though, andany desired random value generation may be used. If the user 2502 hasselected multiple items for purchase, a separate initial probabilityvalue may be determined for each item, or a single initial probabilityvalue may be determined for the entire purchase (e.g., one probabilityvalue for all items in the user's checkout cart).

The initial probability value may be used to determine if the user 2502qualifies for a loot. For example, if the initial probability value maybe between 00.0 and 91.9, the user may not be eligible for a loot item.An initial probability value between 92.0 and 97.9 may result in theuser 2502 being granted an item from the available loot inventory withthe loot class “good.” An initial probability value between 98.0 and99.0 may result in the user 2502 being granted an item from theavailable loot inventory with the loot class “rare.” An initialprobability value between 99.1 and 99.5 may result in the user 2502being granted an item from the available loot inventory with the lootclass “superior.” An initial probability value between 99.5 and 100 mayresult in the user 2502 being granted an item from the available lootinventory with the loot class “epic.” Of course, the values and detailsare merely examples, and other probabilities, variations, and items maybe used. Different items may have different probabilities, items mayhave greater or fewer numbers of variants than other items, and othermodifications may be made as desired.

If the user 2502 does not qualify for a loot item based on the initialprobability value, the new purchase process 1058 applies the unexpiredloot scores of the user 2502 to the initial probability value to boostthe value. For example, an initial probability value of 90 may beincreased to 91.8 by applying a loot score of +2%. The new purchaseprocess 1058 may determine if the user 2502 may be eligible for a lootitem based on the increased probably score.

At step 25.4, if the user 2502 may be eligible for a loot item from theavailable loot inventory database 1008 based on the initial probabilityvalue or the increased probability value, the loot item may be displayedto the user by the new purchase process 1032.

At step S25.5, the new purchase process 1032 may receive an indicationfrom a user 2502 to acquire the displayed loot item. For example, theindication may be sent to the new purchase process 1058 if the user mayselect the “Great!” button 206 in FIG. 2C to accept and/or purchase theloot item. At step S25.5, the new purchase process 1032 may execute thepurchase of the loot item and/or records the purchase transaction in thepurchase records database 1012. The new purchase process 1032 may alsorecord ownership of the loot item by the owner 2502 in the loot itemownership registry database 1010.

FIG. 26 an example workflow 2600 that illustrates a representativemethod of receiving a loot item during purchase of a common item from aretailer 2604 outside the loot system 922 or the loot server 921. Theworkflow 2600 starts at step S26.1 where the user 2602 may provide userID and login credentials to access the loot system 922 to the retailer2604. The user 2602 may be assigned an electronic rewards “card” such asa cookie, profile, and/or other tag in a user's personal device and/orthe user's account in the retailer 2604 may be tagged to the user'saccount/profile in the loot system 922. At step 26.2, the retailer 2604displays available inventory to the user 2602. At step 26.3, theretailer 2604 receives an indication from the user 2602 to purchase anitem. At step 26.4, the retailer 2604 sends a request to the externalpurchase process 1056 in the loot system 922 to determine theeligibility of the user 2602 to acquire a loot item. At step S26.5, theexternal purchase process 1056 may determine the unexpired loot scoresfor the user 2602 from the user loot score database 1120.

At step S26.6, the external purchase process 1056 may determine if theuser 2602 may be eligible for a loot item based on the unexpired lootscores of the user. The external purchase process 1056 may generate aninitial probability value to determine which version of an item the user2602 may receive. If the user 2502 does not qualify for a loot itembased on the initial probability value, the external purchase process1056 applies the unexpired loot scores of the user 2602 to the initialprobability value to boost the value. For example, an initialprobability value of 90 may be increased to 91.8 by applying a lootscore of +2%. The external purchase process 1056 may determine if theuser 2502 may be eligible for a loot item based on the increasedprobably score.

At step S26.7, the external purchase process 1056 may send an indicationto the retailer 2604 whether the user 2602 may be eligible for a lootitem and if so, which class of loot item may be presented to the user.At step S26.8, if the user is eligible for a loot item, the retailer2604 displays the loot item to the user 2602.

At step S26.9, the retailer 2604 may receive an indication from the user2602 to acquire the displayed loot item. At step S26.10, the retailermay execute the purchase transaction and may send a record of thepurchase to the external purchase process 1056. At step S26.11, theexternal purchase process 1056 may record ownership of the loot item bythe owner 2602 in the loot item ownership registry database 1010.

FIG. 27 is an example workflow 2700 that illustrates a representativemethod of exchanging loot items in the internal retail store 1030 of theloot system 922. The workflow 2700 starts at step S27.1 where theexchange process 1034 in the internal retail store 1030 may receive anindication from a user 2702 to exchange a loot item A for loot item B.At step 26.3, the exchange process 1034 may determine if the loot item Bmay be available in the available loot item inventory database 1008 andwhether the loot item A and the loot item B may have similar lootclasses and item description. For example, a black sweatshirt with theloot class “rare” may be exchanged with a red sweatshirt with the lootclass “rare.” The black sweatshirt with the loot class “rare” may not beexchanged with a black sweatshirt with the loot class “superior.” Atstep S27.4, if the loot item B may be available in the available lootitem inventory database 1008 and the loot item A and the loot item Bhave similar loot classes and item descriptions, the exchange process1034 executes the exchange transaction and records the transaction inthe exchange records database 1016. At step S26.11, the exchange process1034 records ownership of the loot item B by the owner 2702 in the lootitem ownership registry database 1010 and updates ownership of the lootitem A to indicate that it may be no longer owned by the user 2702.

Ownership of a variant item may be tracked, and this may facilitatesubsequent transfers of the item, as users may choose to sell theiritems as collectible items on a marketplace (e.g., in one of the retailplatforms 912, and/or another online marketplace). FIG. 28 is an exampleworkflow 2800 that illustrates a representative method of requestingchange in ownership of a loot item in the loot system 922. The workflow2800 starts at step S28.1 where the loot ownership process 1052 receivesan indication from a user 2802 to record new ownership of a loot itemwith an authorization tag ABCD. The user 2802 may verify that the lootitem is indeed the one in the registry through an authentication tag(e.g., by visual inspection, scanning a bar code and/or embedded RFIDtag, etc.). At step 28.2, the loot ownership process 1052 retrieves theownership record of the loot item through the authentication tag fromthe loot item ownership registry database 1010 and records the newownership of the loot item by the owner 2802.

With all workflows described herein, it will be appreciated that many ofthe steps may be combined, performed in parallel, or performed in adifferent sequence without affecting the functions achieved. In somecases, as the reader will appreciate, a re-arrangement of steps willachieve the same results only if certain other changes are made as well.In other cases, as the reader will appreciate, a re-arrangement of stepswill achieve the same results only if certain conditions are satisfied.Furthermore, it will be appreciated that the flow charts herein showonly steps that are pertinent to an understanding of the invention, andit will be understood that numerous additional steps for accomplishingother functions can be performed before, after and between those shown.

The invention claimed is:
 1. A method comprising: establishing, by acomputing device, communications with a social media server, a retailserver, a sport streaming server, a gaming server, and a content server;receiving, by the computing device and via the communications, behaviordata associated with one or more user devices of a user account, whereinthe behavior data comprises: social media behavior data from the socialmedia server, purchase history data from the retail server, streaminglive match participation data from the sport streaming server, gamingbehavior data from the gaming server, and content viewing history datafrom the content server; inputting, by the computing device and into amachine learning model, the behavior data; receiving, by the computingdevice and from the machine learning model, information indicating aprobability value boost; based on receiving, from the one or more userdevices, a selection, associated with the user account, of a commonitem, generating, by the computing device, a random probability valueusing a random probability generator; updating, by the computing deviceand based on the probability value boost, the random probability value;and causing, by the computing device and based on a comparison of theupdated random probability value with an acquisition value of a rarerversion of the common item, display of a user interface indicating thatthe rarer version of the common item is available to the user account.2. The method of claim 1, further comprising: determining geospatialcoordinates of the one or more user devices; determining whether thegeospatial coordinates are within a threshold distance of a place ofinterest; and updating, based on a determination that the geospatialcoordinates are within the threshold distance of the place of interest,the probability value boost.
 3. The method of claim 1, furthercomprising: identifying, from the streaming live match participationdata, an indication of participation of the user account in a livebroadcast of a gaming event; and determining, based on the indication ofthe participation of the user account in the live broadcast, theprobability value boost.
 4. The method of claim 1, further comprising:identifying, from the gaming behavior data, information indicating aquantity of time spent by the user account interacting with the gamingserver; identifying, from the gaming behavior data, informationindicating game winning events associated with the user account; anddetermining, based on the information indicating the quantity of timespent by the user account interacting with the gaming server or based onthe information indicating the game winning events associated with theuser account, the probability value boost.
 5. The method of claim 1,further comprising: identifying, from the purchasing history data,information indicating purchasing behavior of the user account;identifying, from the purchasing history data, an object or a phrase ina picture posted via the retail server and associated with the useraccount; and determining, based on the information indicating thepurchasing behavior of the user account, on the identified object, or onthe identified phrase, the probability value boost.
 6. The method ofclaim 1, further comprising: identifying, from the social media behaviordata, images and phrases associated with the user account; identifying,by analyzing pixel frames of the images, one or more objects in theimages; identifying, from the phrases and by using heuristics-basedstring analysis, key terms in the phrases; determining, from the socialmedia behavior data, a quantity of contacts associated with the useraccount in the social media server; and determining, based on thequantity of contacts, on the one or more objects in the images, or onthe key terms in the phrases, the probability value boost.
 7. The methodof claim 1, further comprising: prior to receiving the selection of thecommon item, sending, to the one or more user devices and based on thebehavior data, information indicating one or more rarer versions of thecommon item.
 8. The method of claim 1, further comprising: receivingsecond behavior data of associated with one or more user devices of asecond user account, wherein the second behavior data comprises one ormore of: data from the social media server, data from the retail server,data from the sport streaming server, data from the gaming server, ordata from the content server; inputting, into the machine learningmodel, the second behavior data; and receiving, from the machinelearning model, information indicating a second probability value boost,wherein updating the random probability value comprises updating, basedon the probability value boost and the second probability value boost,the random probability value.
 9. The method of claim 1, furthercomprising: receiving, from the one or more user devices associated withthe user account, device data associated with the user account;inputting, into the machine learning model, the device data; andreceiving, from the machine learning model, information indicating asecond probability value boost, wherein updating the random probabilityvalue comprises updating, based on the probability value boost and thesecond probability value boost, the random probability value.
 10. Anon-transitory computer readable medium storing instructions that, whenexecuted, cause: establishing communications with a social media server,a retail server, a sport streaming server, a gaming server, and acontent server; receiving, via the communications, behavior dataassociated with one or more user devices of a user account, wherein thebehavior data comprises: social media behavior data from the socialmedia server, purchase history data from the retail server, streaminglive match participation data from the sport streaming server, gamingbehavior data from the gaming server, and content viewing history datafrom the content server; inputting, into a machine learning model, thebehavior data; receiving, from the machine learning model, informationindicating a probability value boost; based on receiving, from the oneor more user devices, a selection, associated with the user account, ofa common item, generating a random probability value using a randomprobability generator; updating, based on the probability value boost,the random probability value; and causing, based on a comparison of theupdated random probability value with an acquisition value of a rarerversion of the common item, display of a user interface indicating thatthe rarer version of the common item is available to the user account.11. The non-transitory computer readable medium of claim 10, wherein theinstructions, when executed, further cause: determining geospatialcoordinates of the one or more user devices; determining whether thegeospatial coordinates are within a threshold distance of a place ofinterest; and updating, based on a determination that the geospatialcoordinates are within the threshold distance of the place of interest,the probability value boost.
 12. The non-transitory computer readablemedium of claim 10, wherein the instructions, when executed, furthercause: identifying, from the streaming live match participation data, anindication of participation of the user account in a live broadcast of agaming event; and determining, based on the indication of theparticipation of the user account in the live broadcast, the probabilityvalue boost.
 13. The non-transitory computer readable medium of claim10, wherein the instructions, when executed, further cause: identifying,from the gaming behavior data, information indicating a quantity of timespent by the user account interacting with the gaming server;identifying, from the gaming behavior data, information indicating gamewinning events associated with the user account; and determining, basedon the information indicating the quantity of time spent by the useraccount interacting with the gaming server or based on the informationindicating the game winning events associated with the user account, theprobability value boost.
 14. The non-transitory computer readable mediumof claim 10, wherein the instructions, when executed, further cause:identifying, from the purchasing history data, information indicatingpurchasing behavior of the user account; identifying, from thepurchasing history data, an object or a phrase in a picture posted viathe retail server and associated with the user account; and determining,based on the information indicating the purchasing behavior of the useraccount, on the identified object, or on the identified phrase, theprobability value boost.
 15. The non-transitory computer readable mediumof claim 10, wherein the instructions, when executed, further cause:identifying, from the social media behavior data, images and phrasesassociated with the user account; identifying, by analyzing pixel framesof the images, one or more objects in the images; identifying, from thephrases and by using heuristics-based string analysis, key terms in thephrases; determining, from the social media behavior data, a quantity ofcontacts associated with the user account in the social media server;and determining, based on the quantity of contacts, on the one or moreobjects in the images, or on the key terms in the phrases, theprobability value boost.
 16. The non-transitory computer readable mediumof claim 10, wherein the instructions, when executed, further cause:prior to receiving the selection of the common item, sending, to the oneor more user devices and based on the behavior data, informationindicating one or more rarer versions of the common item.
 17. Thenon-transitory computer readable medium of claim 10, wherein theinstructions, when executed, further cause: receiving second behaviordata of associated with one or more user devices of a second useraccount, wherein the second behavior data comprises one or more of: datafrom the social media server, data from the retail server, data from thesport streaming server, data from the gaming server, or data from thecontent server; inputting, into the machine learning model, the secondbehavior data; and receiving, from the machine learning model,information indicating a second probability value boost, wherein theinstructions, when executed, cause updating the random probability valueby updating, based on the probability value boost and the secondprobability value boost, the random probability value.
 18. Thenon-transitory computer readable medium of claim 10, wherein theinstructions, when executed, further cause: receiving, from the one ormore user devices associated with the user account, device dataassociated with the user account; inputting, into the machine learningmodel, the device data; and receiving, from the machine learning model,information indicating a second probability value boost, and wherein theinstructions, when executed, cause updating the random probability valueby updating, based on the probability value boost and the secondprobability value boost, the random probability value.
 19. An apparatuscomprising: one or more processors; and memory storing instructionsthat, when executed by the one or more processors, cause the apparatusto: establish communications with a social media server, a retailserver, a sport streaming server, a gaming server, and a content server;receive, via the communications, behavior data associated with one ormore user devices of a user account, wherein the behavior datacomprises: social media behavior data from the social media server,purchase history data from the retail server, streaming live matchparticipation data from the sport streaming server, gaming behavior datafrom the gaming server, and content viewing history data from thecontent server; input, into a machine learning model, the behavior data;receive, from the machine learning model, information indicating aprobability value boost; based on receiving, from the one or more userdevices, a selection, associated with the user account, of a commonitem, generate a random probability value using a random probabilitygenerator; update, based on the probability value boost, the randomprobability value; and cause, based on a comparison of the updatedrandom probability value with an acquisition value of a rarer version ofthe common item, display of a user interface indicating that the rarerversion of the common item is available to the user account.
 20. Theapparatus of claim 19, wherein the instructions, when executed by theone or more processors, further cause the apparatus to: determinegeospatial coordinates of the one or more user devices; determinewhether the geospatial coordinates are within a threshold distance of aplace of interest; and update, based on a determination that thegeospatial coordinates are within the threshold distance of the place ofinterest, the probability value boost.
 21. The apparatus of claim 19,wherein the instructions, when executed by the one or more processors,further cause the apparatus to: identify, from the streaming live matchparticipation data, an indication of participation of the user accountin a live broadcast of a gaming event; and determine, based on theindication of the participation of the user account in the livebroadcast, the probability value boost.
 22. The apparatus of claim 19,wherein the instructions, when executed by the one or more processors,further cause the apparatus to: identify, from the gaming behavior data,information indicating a quantity of time spent by the user accountinteracting with the gaming server; identify, from the gaming behaviordata, information indicating game winning events associated with theuser account; and determine, based on the information indicating thequantity of time spent by the user account interacting with the gamingserver or based on the information indicating the game winning eventsassociated with the user account, the probability value boost.
 23. Theapparatus of claim 19, wherein the instructions, when executed by theone or more processors, further cause the apparatus to: identify, fromthe purchasing history data, information indicating purchasing behaviorof the user account; identify, from the purchasing history data, anobject or a phrase in a picture posted via the retail server andassociated with the user account; and determine, based on theinformation indicating the purchasing behavior of the user account, onthe identified object, or on the identified phrase, the probabilityvalue boost.
 24. The apparatus of claim 19, wherein the instructions,when executed by the one or more processors, further cause the apparatusto: identify, from the social media behavior data, images and phrasesassociated with the user account; identify, by analyzing pixel frames ofthe images, one or more objects in the images; identify, from thephrases and by using heuristics-based string analysis, key terms in thephrases; determine, from the social media behavior data, a quantity ofcontacts associated with the user account in the social media server;and determine, based on the quantity of contacts, on the one or moreobjects in the images, or on the key terms in the phrases, theprobability value boost.
 25. The apparatus of claim 19, wherein theinstructions, when executed by the one or more processors, further causethe apparatus to: prior to receiving the selection of the common item,send, to the one or more user devices and based on the behavior data,information indicating one or more rarer versions of the common item.26. The apparatus of claim 19, wherein the instructions, when executedby the one or more processors, further cause the apparatus to: receivesecond behavior data associated with one or more user devices of asecond user account, wherein the second behavior data comprises one ormore of: data from the social media server, data from the retail server,data from the sport streaming server, data from the gaming server, ordata from the content server; input, into the machine learning model,the second behavior data; and receive, from the machine learning model,information indicating a second probability value boost, and wherein theinstructions, when executed by the one or more processors, further causethe apparatus to update the random probability value by updating, basedon the probability value boost and the second probability value boost,the random probability value.
 27. The apparatus of claim 19, wherein theinstructions, when executed by the one or more processors, further causethe apparatus to: receive, from the one or more user devices associatedwith the user account, device data associated with the user account;input, into the machine learning model, the device data; and receive,from the machine learning model, information indicating a secondprobability value boost, and wherein the instructions, when executed bythe one or more processors, further cause the apparatus to update therandom probability value by updating, based on the probability valueboost and the second probability value boost, the random probabilityvalue.